The DOI matches its Crossref record; 272 of the 286 references it cites were found in a registry or an index; 85 of the 336 sources its claims cite were checked for support.
Inductive Logic Programming At 30: A New Introduction
Open accessAbstract
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypothesis (a set of logical rules) that generalises training examples. As ILP turns 30, we provide a new introduction to the field. We introduce the necessary logical notation and the main learning settings; describe the building blocks of an ILP system; compare several systems on several dimensions; describe four systems (Aleph, TILDE, ASPAL, and Metagol); highlight key application areas; and, finally, summarise current limitations and directions for future research.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This paper is a new introduction to inductive logic programming (ILP) on its 30th anniversary, covering logical notation, learning settings, system design choices, comparisons, four case studies, applications, and open limitations. It argues ILP remains distinctive for learning interpretable relational and recursive logic programs from few examples, while identifying usability, language bias, predicate invention, lifelong learning, noisy background knowledge, and raw-data perception as key challenges.
Key findings
- ILP induces hypotheses as logic programs; unlike table-based ML, it represents examples, background knowledge, and hypotheses as logic programs and learns relations, with strengths in data efficiency, recursion, predicate invention, and knowledge transfer.
- The survey compares systems on learning setting, hypothesis class, background knowledge, language bias, and search method, and on features including noise, optimality, infinite domains, recursion, and predicate invention; it details Aleph, TILDE, ASPAL, and Metagol.
- Applications discussed include bioinformatics and drug design, the Robot Scientist (reported as the first machine to independently discover new scientific knowledge), ecology, program analysis, data curation and string transformations, learning from trajectories, NLP, physics-informed learning, robotics, and games.
- Reported figures include: over 100 ILP systems built since 1991 but less than a handful meaningfully usable; Lin et al. learn 17 string transformation tasks over time; Knorf reduces the number of literals in a program by 50% or more; and the basic Metagol implementation is less than 100 lines of Prolog code.
Methods
- This is a survey/tutorial, not an empirical study. It introduces logic programming notation, formalizes learning from entailment and interpretations, describes ILP system building blocks, compares systems in tables, presents four case studies, surveys applications and related work, and summarizes limitations.
- It uses illustrative scenarios and examples—such as the happy/lego concept, last-element and quicksort programs, drug design, Bongard problems, kinship, machine repair, and ASPAL’s penguin example—rather than a dataset or experimental evaluation.
- The main analysis is conceptual synthesis and qualitative comparison; no new experiments or benchmark results are reported.
Limitations
- The paper states that ILP tools are often hard to use and poorly engineered; language biases are brittle and difficult to choose; predicate invention and abstraction remain difficult; lifelong learning, relevance, noisy background knowledge, probabilistic ILP, explainability, and learning from raw data are unresolved or under-explored.
- The paper states its scope is mostly definite programs, especially Prolog, and mostly recent developments; it does not detail work combining neural networks with ILP, and its comparison tables exclude many systems such as interactive, theory revision, and probabilistic systems.
- Evident from the text: as a survey/tutorial, it provides no empirical validation of its comparative claims, and the tables are explicitly described as coarse, high-level overviews that “should not be taken absolutely literally.”
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Claims the paper makes
164 Own interpretation · 102 Sources not found · 95 No basis given · 42 No full text of the sources · 30 Partly supported · 27 Supported · 23 Not checked yet · 9 Supported so far · 3 Own result · 2 Couldn’t confirm · 1 Mixed support · accuracy not yet measured
Some cited sources support this claim and some don’t — read each source’s verdict below.
In the paper
“However, this placeholder approach is limited because it requires that a user manually specify the arity and argument types of a symbol (Law et al., 2014), which rather defeats the point, or requires generating all possible invented predicates (Evans & Grefenstette, 2018; Evans et al., 2021), which is computationally expensive.”
What the sources say
- Disputedcites Evans & Grefenstette, 2018 sourceExperimental — accuracy not yet measured
Section 3.1 (page unavailable) says the program template specifies the set of invented predicates and the arity of each. Section 3.2 says the system generates clauses satisfying each rule template, subject to restrictions—not all possible invented predicates. Section 7.1 describes exhaustive enumeration of program templates only as a separate, computationally intensive experiment. (LLM, conf=0.84)
Checked by a reasoning model — may be wrong.
- Partly supportedcites Evans et al., 2021 sourceExperimental — accuracy not yet measured
Section 4.1, “Iterating through templates” (page unavailable), says the method enumerates templates that include sets of predicates. But it explicitly says it cannot enumerate all such tuples because there are infinitely many; it uses a bound that increases gradually instead. Section 4.4 discusses computational cost, but does not establish that all possible invented predicates must be generated. (LLM, conf=0.85)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Disputed
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“By contrast, because of its symbolic representation, ILP naturally supports lifelong and transfer learning (Torrey et al., 2007; Cropper, 2019), which is considered essential for human-like AI (Lake et al., 2016).”
What the sources say
- Not matchedcites Torrey et al., 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Partly supportedcites Cropper, 2019 sourceExperimental — accuracy not yet measured
The Related Work section (page unavailable) says that ILP meta-learning saves learned programs as background knowledge for reuse on unsolved tasks, supporting learning over time and transfer between tasks. The paper does not attribute that capability specifically to ILP’s symbolic representation or establish it as a natural property of ILP generally; it describes particular approaches that implement it. (LLM, conf=0.83)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For instance, it is impossible to provide a decision tree learner (Quinlan, 1986, 1993) this infinite relation because it would require an infinite feature table.”
What the sources say
- Supportedcites Quinlan, 1986 source
The citation identifies a decision-tree learner, rather than attributing the infinite-table argument to Quinlan. Section 3, “The induction task” (page unavailable), describes ID3 as forming decision trees from training sets of objects described by attributes, so it supports that identification. (LLM, conf=0.88)
- Not matchedcites Quinlan, 1993
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“If learning to recognise events, a user could provide the axioms of the event calculus (Katzouris et al., 2015).”
What the sources say
- Supportedcites Katzouris et al., 2015 source
In Example 1 (page unavailable), the paper says the input for learning includes the axioms of Simplified Discrete Event Calculus as background knowledge. Section 2.1 identifies these as Event Calculus axioms. The paper does not explicitly name a user as the provider, but supplying those axioms as input is consistent with the claim. (LLM, conf=0.89)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Many forms of ML are notorious for their inability to generalise from small numbers of training examples, notably deep learning (Marcus, 2018; Chollet, 2019; Bengio et al., 2019).”
What the sources say
- Supportedcites Marcus, 2018 source
Marcus supports the claim as it applies to deep learning. Section 3 (p. 5) says neural networks generally need large amounts of data to generalize well, and §3.1 (p. 7) says deep learning is often not an ideal solution when data are limited. (LLM, conf=0.92)
- Supportedcites Chollet, 2019 source
Section II.1.1 (p. 20) says contemporary deep-learning models require dense sampling of the training space to achieve high skill. This supports the claim that deep learning, in particular, struggles to generalise from few examples. (LLM, conf=0.89)
- Partly supportedcites Bengio et al., 2019 sourceExperimental — accuracy not yet measured
The Introduction (p. 1) says current machine-learning methods seem weak at generalizing beyond the training distribution. Section 2.2.1 (p. 5) discusses how the number of examples needed for adaptation relates to model complexity, including for neural networks. Neither passage establishes the broader claim that deep learning is generally unable to generalize from small training sets; the paper's few-example discussion concerns adaptation to a related distribution. (LLM, conf=0.78)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Some systems induce full (unrestricted) clausal theories, such as Claudien (De Raedt & Dehaspe, 1997) and CF-induction (Inoue, 2004).”
What the sources say
- Supportedcites De Raedt & Dehaspe, 1997 source
The Abstract (page unavailable) identifies Claudien as an ILP engine whose induced regularities are represented by clausal theories. The Language Assumption example (page unavailable) includes a clause with two head literals, supporting “unrestricted” in the sense of not being limited to definite clauses. This citation identifies Claudien; it does not need to establish the separate claim about CF-induction. (LLM, conf=0.88)
- Supportedcites Inoue, 2004 source
Section 4.4 states that CF-induction can derive a non-Horn hypothesis, and Section 7 describes it as a method for finding hypotheses from full clausal theories. This supports the part of the sentence attributed to Inoue (2004): CF-induction can induce full clausal theories. (LLM, conf=0.91)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“However, it is often difficult and expensive to obtain such BK.”
What the sources say
- Could not verifycites Evans & Grefenstette, 2018 sourceExperimental — accuracy not yet measured
Section 5.3.1 describes background knowledge as arithmetic facts supplied for a task, but does not discuss the difficulty or expense of obtaining them. Section 7.1 calls hand-engineering program templates difficult work; those templates are distinct from the background knowledge. Searches for the cost of obtaining background knowledge found no supporting passage. (LLM, conf=0.73)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: ILP has traditionally relied on predefined and hand-crafted background knowledge, often designed by domain experts.
- Could not verify
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For this reason, there is preliminary work in reasoning about metarules to identify universal sets suitable to learn certain fragments of logic programs (Cropper & Muggleton, 2014; Tourret & Cropper, 2019; Cropper & Tourret, 2020).”
What the sources say
- Not matchedcites Cropper & Muggleton, 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Tourret & Cropper, 2019 source
The Motivation section says the paper studies derivation reducibility in logic fragments relevant to ILP in order to reduce sets of metarules. The Conclusion frames the question as whether finite sets of such clauses could enable learning any program in a specified fragment, and reports a negative result for one fragment. This supports the claim that the paper is preliminary work investigating suitable universal sets, not that it identified one. (LLM, conf=0.90)
- Supportedcites Cropper & Tourret, 2020 source
Section 2.1 says the paper aims to identify minimal sets of metarules for fragments such as Datalog, from which a learner can theoretically learn any program in the fragment. The Abstract describes its logical reduction of metarules for fragments relevant to inductive logic programming. Page numbers are not provided in our copy. (LLM, conf=0.92)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“A third new approach has recently emerged called meta-level ILP (Inoue et al., 2013; Muggleton et al., 2015; Inoue, 2016; Law et al., 2020; Cropper & Morel, 2021).”
What the sources say
- Not matchedcites Inoue et al., 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Muggleton et al., 2015 source
The Introduction (p. 2) identifies meta-interpretive learning (MIL) as an ILP technique built around a meta-interpreter. Related Work (p. 4) contrasts this approach with earlier ILP approaches to predicate invention, supporting its use as an example of the newer meta-level approach. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Inoue, 2016
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
Every source the paper cites for this claim was checked and supports it.
In the paper
“To avoid this issue, these systems rely on lookahead (Struyf et al., 2006) which increases the complexity of learning.”
What the sources say
- Supportedcites Struyf et al., 2006 source
The Introduction states that execution time increases exponentially with lookahead depth. The Conclusions likewise say lookahead incurs an exponential increase in execution time, supporting the claim that it increases the computational complexity of learning. (LLM, conf=0.93)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
- Probably not a substantial claim. 274
- It may state two separate claims as one. 101
- The quote only partly states this claim. 2
Every source the paper cites for this claim was checked and supports it.
In the paper
“which is considered essential for human-like AI (Lake et al., 2016).”
What the sources say
- Supportedcites Lake et al., 2016 source
Section 4.2 treats transfer and learning-to-learn as important to making AI learn new tasks with human-like speed and flexibility. Sections 6.2 and 6.3 likewise describe learning new concepts as they are encountered and reusing knowledge across tasks as goals for human-like AI. Together, these support the paraphrase, although the authors do not use the phrase “lifelong and transfer learning” as a single requirement. (LLM, conf=0.85)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Because of the expressivity of logic programs, ILP can learn complex relational theories, such as cellular automata (Inoue et al., 2014; Evans et al., 2021), event calculus theories (Katzouris et al., 2015), and Petri nets (Bain & Srinivasan, 2018), and various forms of non-monotonic programs (Bain & Muggleton, 1991; Inoue & Kudoh, 1997; Sakama, 2001).”
What the sources say
- Not matchedcites Inoue et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Evans et al., 2021 source
The Evans et al. citation is attached to the cellular-automata example, not the other examples in the sentence. In §5.1.2 (page unavailable), the paper reports that its symbolic Apperception Engine inferred dynamics from elementary cellular-automaton sequences and correctly predicted 249 of 256 trajectories. Section 5.2.4 distinguishes that system from ILASP, which could not solve the ECA tasks because of memory requirements; the paper therefore supports the example of learning cellular-automaton dynamics, not a claim that ILASP solved those tasks. (LLM, conf=0.87)
- Supportedcites Katzouris et al., 2015 source
The citation is attached specifically to “event calculus theories,” not to the sentence’s other examples. Section 2.2 states that ILP is used to learn event definitions in the form of domain-specific Event Calculus axioms. (LLM, conf=0.93)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Prolog (Kowalski, 1988; Colmerauer & Roussel, 1993) is a logic programming language based on SLD-resolution and is therefore restricted to Horn clauses.”
What the sources say
- Partly supportedcites Kowalski, 1988 sourceExperimental — accuracy not yet measured
In “The Edinburgh–Marseilles” (page unavailable), Kowalski identifies SLD-resolution as a procedure for Horn clauses and associates Prolog with logic programming using the Horn-clause subset. The passages do not explicitly say that Prolog is based on SLD-resolution or that it is restricted to Horn clauses; the latter is stronger than the source establishes. (LLM, conf=0.78)
- Partly supportedcites Colmerauer & Roussel, 1993 sourceExperimental — accuracy not yet measured
In “Colmerauer and Roussel” (p. 3), the authors describe choosing linear resolution and say the strategy is complete when only Horn clauses are used. “Part IV. The final Prolog” (p. 10) also describes Prolog as resolution-based. These passages do not establish that Prolog is restricted to Horn clauses; the copy calls the method SL-resolution rather than SLD-resolution. (LLM, conf=0.84)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Quinlan's (1990) FOIL system is one of the most well-known ILP systems and is a natural extension of ID3 (Quinlan, 1986) from the propositional setting to the first-order setting.”
What the sources say
- Supportedcites Quinlan, 1990 source
Section 4 identifies FOIL as Quinlan’s system, traces its ancestry to ID3, and says it uses an information-based search heuristic like ID3. The Abstract and Discussion describe its adaptation of attribute-value learning techniques to a first-order formalism. “One of the most well-known” is the citing authors’ characterization, not a finding attributed to the 1990 paper. (LLM, conf=0.88)
- Supportedcites Quinlan, 1986 source
The 1986 citation is attached to ID3, not to the claims about FOIL. The Introduction identifies ID3 as a Quinlan program, and Section 3 describes its decision-tree method using attributes of objects. This supports the citation’s identification of ID3 in the sentence. (LLM, conf=0.91)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“A third approach has recently emerged called meta-level ILP (Inoue et al., 2013; Muggleton et al., 2015; Inoue, 2016; Law et al., 2020; Cropper & Morel, 2021).”
What the sources say
- Not matchedcites Inoue et al., 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Muggleton et al., 2015 source
The Introduction (p. 2) identifies meta-interpretive learning (MIL) as an ILP technique built around a meta-interpreter. Related Work (p. 4) contrasts it with earlier ILP approaches, supporting its citation as an example of the newer meta-level approach. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Inoue, 2016
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Other recent work focuses on learning from transitions (Inoue et al., 2014; Evans et al., 2021; Ribeiro et al., 2020) and learning from answer sets (Law et al., 2014).”
What the sources say
- Not matchedcites Inoue et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Evans et al., 2021 source
Evans et al. describe their own task as constructing rules and other model components from a sequence of observed states (§7.2, page not provided). That supports citing this paper as an example of work on learning from transitions. The separate claim about learning from answer sets is attached to Law et al., not Evans et al. (LLM, conf=0.90)
- Not checked — no full text of the sourcecites Law et al., 2014 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“LFE is by far the most popular ILP setting (Shapiro, 1983; Muggleton, 1987; Muggleton & Buntine, 1988; Muggleton & Feng, 1990; Quinlan, 1990; Muggleton, 1995; Bratko, 1999; Srinivasan, 2001; Ray, 2009; Ahlgren & Yuen, 2013; Muggleton et al., 2015; Cropper & Muggleton, 2016; Kaminski et al., 2018; Cropper & Morel, 2021).”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
- Not checked — no full text of the sourcecites Muggleton, 1987
- Partly supportedcites Cropper & Morel, 2021 sourceExperimental — accuracy not yet measured
Section 3.2 (p. 11) says the paper’s problem setting is based on ILP learning from entailment, so the source is an example of that setting. It does not say that learning from entailment is the most popular ILP setting, let alone by far. (LLM, conf=0.82)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The second most popular (De Raedt & Dehaspe, 1997; Blockeel & De Raedt, 1998; Law et al., 2014) learning setting is LFI where an example is an interpretation, i.e. a set of facts.”
What the sources say
- Partly supportedcites De Raedt & Dehaspe, 1997 sourceExperimental — accuracy not yet measured
Section 3.3.3 states that examples in the paper’s learning-from-interpretations setting are interpretations, and Section 2 describes a Herbrand interpretation as a set of ground facts. Section 3 calls normal inductive logic programming the setting used by the large majority of systems, but does not rank learning from interpretations as the second most popular; its numbered list is a list of formalisations, not a popularity ranking. Page numbers were not available in our copy. (LLM, conf=0.88)
- Partly supportedcites Blockeel & De Raedt, 1998 sourceExperimental — accuracy not yet measured
The Introduction and Section 2 identify the setting as learning from interpretations and describe each example as a Prolog program encoding its properties, supporting the claim about LFI examples. Neither passage establishes that LFI is the second most popular learning setting. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Law et al., 2014 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Evans et al. (2021) use constraints to induce theories to explain sensory sequences.”
What the sources say
- Supportedcites Evans et al., 2021 source
The Introduction describes a symbolic causal theory containing constraints that must explain the sensory sequence. It also says the Apperception Engine synthesizes such a theory from a sensory sequence. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“However, some systems (Shapiro, 1983; Bratko, 1999; Cropper & Morel, 2021) induce theories formed of multiple clauses and thus require generality orders over clausal theories .”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
- Not matchedcites Bratko, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Cropper & Morel, 2021 source
Section 3.1 (p. 10) defines a clausal theory as a set of clauses and uses “program” as a synonym for theory. Section 3.4 (pp. 14–15) extends subsumption to clausal theories and uses it to define generalisation and specialisation of hypotheses, supporting the claim about generality orders for multi-clause theories. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“The above paragraph refers only to generality orders on single clauses, as many systems employ the covering algorithm whereby hypotheses are constructed iteratively clause by clause (Quinlan, 1990; De Raedt & Dehaspe, 1997; Muggleton, 1995; Blockeel & De Raedt, 1998; Srinivasan, 2001).”
What the sources say
- Supportedcites Quinlan, 1990 source
Section 4, “FOIL, a system that constructs definitions” (page unavailable), says FOIL finds clauses one at a time, removing tuples explained by each clause before finding the next. Section 2.2 describes the same repeated covering procedure for the AQ family, supporting the statement that multiple systems use this approach. (LLM, conf=0.93)
- Supportedcites De Raedt & Dehaspe, 1997 source
Section 5.3 says that other inductive logic programming approaches employ Michalski’s covering algorithm. The algorithm description in Section 4 shows a hypothesis being built by adding clauses one at a time, consistent with the citing sentence’s clause-by-clause description. The paper distinguishes those covering approaches from its own Claudien approach. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites Muggleton, 1995 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Top-down algorithms, (Quinlan, 1990; Blockeel & De Raedt, 1998; Bratko, 1999; Muggleton et al., 2008) start with a general hypothesis and then specialise it.”
What the sources say
- Supportedcites Quinlan, 1990 source
Section 4.1 describes FOIL beginning a clause with only its left-hand side, then adding literals to the right-hand side one at a time. That is a top-down progression from a general clause to more specific ones. (LLM, conf=0.91)
- Supportedcites Blockeel & De Raedt, 1998 source
Section 4, “Top-down induction of logical decision trees” (page unavailable), describes TILDE refining a node’s query by adding literals to produce a more specific query. It also states that the refinement operator produces clauses subsumed by the original clause, supporting the general-to-specific description. (LLM, conf=0.88)
- Not matchedcites Bratko, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“∂ ILP (Evans & Grefenstette, 2018) uses neural networks to solve the problem.”
What the sources say
- Partly supportedcites Evans & Grefenstette, 2018 sourceExperimental — accuracy not yet measured
The Introduction and Experiments sections say ∂ILP was connected to a pretrained convolutional neural network to handle ambiguous digit images. Section 4 describes ∂ILP itself as differentiable deduction over weighted logic clauses, so the paper supports neural-network use in that experiment, not as the general mechanism by which ∂ILP solves problems. (LLM, conf=0.82)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“For instance, Metagol (Muggleton et al., 2015; Cropper & Muggleton, 2016) uses a Prolog meta-interpreter to search for a proof of a meta-level Prolog program.”
What the sources say
- Supportedcites Muggleton et al., 2015 source
The Implementation section (p. 8) says Metagol D is built around a Prolog meta-interpreter and uses Prolog backtracking search to find a satisfying solution. The Introduction (p. 2) describes the meta-interpreter proving examples while generating a program hypothesis, supporting the citing sentence’s description of its proof search. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Cropper & Muggleton, 2016 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Law et al. (2020) also provide an overview of conflict-driven ILP, which the systems ILASP3 (Law, 2018) and Popper (Cropper & Morel, 2021) adopt.”
What the sources say
- Not matchedcites Law, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Cropper & Morel, 2021 source
The Abstract (p. 1) describes Popper as an ILP system that learns constraints from failed hypotheses. The Introduction (p. 4) says ILASP3 also uses a generate/test/constrain loop and compares how the two systems derive constraints from failures. This supports the characterization of both as adopting conflict-driven ILP. (LLM, conf=0.90)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Learning efficient logic programs has long been considered a difficult problem (Muggleton & De Raedt, 1994; Muggleton et al., 2012), mainly because there is no declarative difference between an efficient program, such as mergesort, and an inefficient program, such as bubble sort.”
What the sources say
- Partly supportedcites Muggleton & De Raedt, 1994 sourceExperimental — accuracy not yet measured
Section 11.2.1 (p. 668) says that inducing a correct sorting program does not guarantee an efficient one, supporting the difficulty of learning efficient logic programs. It does not say that this difficulty is mainly due to the absence of a declarative difference between efficient and inefficient programs, or use mergesort and bubble sort as examples. (LLM, conf=0.82)
- Not matchedcites Muggleton et al., 2012
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The most common interpretation of an Occamist bias is that amongst all hypotheses consistent with the data, the simplest is the most likely 28 .”
What the sources say
- Partly supportedcites Schaffer, 1993 sourceExperimental — accuracy not yet measured
Section 8.1.1 (page unavailable) says Occam’s statement has sometimes been construed to mean that, other things being equal, simple hypotheses are more likely to be predictive. It does not call this the most common interpretation, and it discusses predictive performance rather than the likelihood that the simplest data-consistent hypothesis is true. (LLM, conf=0.84)
- Not checked — no full text of the sourcecites Domingos (1999) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For instance, TILDE extends a decision tree learner (Quinlan, 1986, 1993) to the first-order setting and uses the same information gain methods to induce hypotheses.”
What the sources say
- Supportedcites Quinlan, 1986 source
Quinlan describes ID3 as a decision-tree learner (Section 4, pp. 7–8) and explains its information-gain criterion for selecting attributes (Section 4, p. 10). The citation identifies the learner and method that the citing authors say TILDE extends; it does not attribute TILDE itself to Quinlan. (LLM, conf=0.90)
- Not matchedcites Quinlan, 1993
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although preliminary work attempts to tackle this issue (Cropper & Morel, 2021; Cropper, 2022), work is still needed for these approaches to scale to very large problems.”
What the sources say
- Supportedcites Cropper & Morel, 2021 source
The citation is attached to the statement that preliminary work attempts to tackle scalability. Section 5.4 (p. 42) explicitly evaluates how Popper scales with the number and size of examples, while §6.1 (p. 45) identifies limitations for future work. The sentence’s conclusion about very large problems is the citing authors’ framing, not a finding attributed specifically to this paper. (LLM, conf=0.88)
- Not matchedcites Cropper, 2022
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“ASP systems (which combine a grounder and a solver), such as Clingo (Gebser et al., 2014), first take a first-order program as input, ground it using an ASP grounder, and then use an ASP solver to determine whether the ground problem is satisfiable.”
What the sources say
- Supportedcites Gebser et al., 2014 source
The Introduction (p. 1) describes standard ASP systems as grounding an input program into a propositional program and then using a solver to compute its stable models; it identifies clingo as combining the gringo grounder and clasp solver. Section 2 (p. 2) says clingo 4 retains this standard behavior by default, although it also permits more flexible control of grounding and solving. (LLM, conf=0.88)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although this approach is shown to improve the grounding problem compared to not using context-dependent examples, the approach still needs a finite grounding for each example and still struggles as the domain size increases (Cropper & Morel, 2021).”
What the sources say
- Partly supportedcites Cropper & Morel, 2021 sourceExperimental — accuracy not yet measured
Section 5.1.1 (p. 33) says the authors used context-dependent examples with ILASP, while Section 2.6 (p. 9) describes finite grounding and difficulty with large domains as limitations of ASP-based approaches. The paper does not show that context-dependent examples improve grounding compared with not using them, or specifically establish a finite-grounding requirement for each such example. (LLM, conf=0.83)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“More precisely, Metagol learns to solve more tasks when using the refactored BK, especially when BK is large.”
What the sources say
- Supportedcites Dumancic et al., 2021 source
The Lego results (Section 5.1, p. 6) say refactoring improves Metagol’s ability to solve tasks when background knowledge (BK) is large (at least 1,000 background tasks). The figure captions (p. 6) also report that Metagol solves more Lego and string-transformation tasks with refactoring. The paper notes a slight degradation for small BK, consistent with the claim’s emphasis on large BK. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Although inverse resolution approaches could support PI, they never demonstrated completeness, partly because of the lack of a declarative bias to delimit the hypothesis space (Muggleton et al., 2015).”
What the sources say
- Supportedcites Muggleton et al., 2015 source
The Related work section (p. 4) identifies early predicate-invention approaches based on inverting resolution and says their completeness was never demonstrated, partly because they lacked a declarative bias to delimit the hypothesis space. This directly supports the attributed paraphrase. (LLM, conf=0.95)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The refactored program is smaller in size and contains fewer redundant clauses.”
What the sources say
- Supportedcites Dumancic et al., 2021 source
The Knowledge Refactoring Problem definition (p. 3) requires the refactored program to be smaller than the original. The Knorf sections (pp. 4–5) state that it minimises both program size and syntactic redundancy between clauses. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“TILDE is a first-order generalisation of decision trees and uses information gain to divide and conquer the training examples.”
What the sources say
- Partly supportedcites Blockeel & De Raedt, 1998 sourceExperimental — accuracy not yet measured
The Introduction and Section 4 describe TILDE as a first-order upgrade of C4.5 that uses top-down, divide-and-conquer decision-tree induction. Section 4 specifies gain ratio, rather than information gain, as TILDE’s split criterion. Page numbers are unavailable in our copy. (LLM, conf=0.88)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“TILDE learns from interpretations, instead of entailment as Aleph, and is an instance of top-down methodology.”
What the sources say
- Supportedcites Blockeel & De Raedt, 1998 source
The Introduction (Section 1) says the authors’ framework learns from interpretations and identifies TILDE as its implementation. Section 4 explicitly presents TILDE as a system in the learning-from-interpretations setting that uses a top-down decision-tree algorithm. (LLM, conf=0.94)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“TILDE learns from interpretations, instead of entailment as Aleph, and is an instance of top-down methodology.”
What the sources say
- Supportedcites Blockeel & De Raedt, 1998 source
The Abstract describes a framework for top-down induction of logical decision trees and identifies TILDE as its implementation. Section 4 further states that TILDE employs the basic top-down decision-tree induction algorithm. (LLM, conf=0.94)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“For instance, Bohan et al. (2011) use ILP to generate plausible and testable hypotheses for trophic relations ('who eats whom') from ecological data.”
What the sources say
- Supportedcites Bohan et al., 2011 source
The Introduction explicitly says the authors use ILP to derive trophic hypotheses and that A/ILP generates plausible, testable hypotheses about ‘who eats whom’ from ecological data. The Results also describe the generated ‘eats’ relations as links that could be tested against literature or by experimentation. Page numbers are not supplied in our copy. (LLM, conf=0.95)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“There has been much recent work on applying ILP in ecology (Bohan et al., 2011; Tamaddoni-Nezhad et al., 2014; Bohan et al., 2017).”
What the sources say
- Supportedcites Bohan et al., 2011 source
The Introduction describes this paper's application of abductive ILP to ecological data to discover trophic links. As one of several citations, it supports the sentence by providing an example of ILP applied in ecology. (LLM, conf=0.91)
- Not matchedcites Tamaddoni-Nezhad et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Bohan et al., 2017 source
The “New Tools to Accelerate Network Characterisation” section says logic-based machine learning has recently been applied in ecology. Box 1 describes its use in ecological network reconstruction, and the References list several ecological applications, supporting the broad statement about recent ILP work. (LLM, conf=0.87)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“ASPAL builds on TAL (Corapi et al., 2010),”
What the sources say
- Could not verifycites Corapi et al., 2010 sourceExperimental — accuracy not yet measured
The Introduction and Section 5 describe TAL and its implementation, but do not mention ASPAL or say that it builds on TAL. Searches for “ASPAL” and for a successor relationship found no passage addressing the claim. (LLM, conf=0.76)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Could not verify
Every source the paper cites for this claim was checked and supports it.
In the paper
“learning protein folding signatures (Turcotte et al., 2001)”
What the sources say
- Supportedcites Turcotte et al., 2001 source
In “Molecular biology motivation,” the authors explicitly present an ILP application to learn rules identifying structural signatures of protein folds. Section 4.1 describes a fold rule generated by the ILP system Progol. This supports the citing phrase “learning protein folding signatures.” (LLM, conf=0.94)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“ILP systems have proven effective in learning SQL queries (Albarghouthi et al., 2017; Sivaraman et al., 2019)”
What the sources say
- Not checked — no full text of the sourcecites Albarghouthi et al., 2017 source
- Partly supportedcites Sivaraman et al., 2019 sourceExperimental — accuracy not yet measured
The Approach section says ALICE uses ILP to learn logical Prolog queries for code search, and the Introduction reports strong code-search results. Neither establishes that ILP systems have proven effective at learning SQL queries; the only SQL-query work found appears in the References. (LLM, conf=0.83)
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
Every source the paper cites for this claim was checked and supports it.
In the paper
“modelling inhibition in metabolic networks (Tamaddoni-Nezhad et al., 2006)”
What the sources say
- Supportedcites Tamaddoni-Nezhad et al., 2006 source
The Introduction states that the authors use Inductive Logic Programming (ILP), alongside abduction, to model inhibition in metabolic networks. This directly supports the citation’s identification of an ILP application. (LLM, conf=0.95)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Other applications include code search (Sivaraman et al., 2019), in which an ILP system interactively learns a search query from examples”
What the sources say
- Supportedcites Sivaraman et al., 2019 source
The Introduction describes ALICE as an interactive code-search technique that infers a search pattern from user feedback and refines it using labeled positive and negative examples. Section III.A says ALICE uses inductive logic programming to construct a logical query for the code the user seeks. (LLM, conf=0.94)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The main advantages of neural approaches are that they can handle noisy BK, as illustrated by ∂ ILP, and can harness tremendous computational power (Ellis et al., 2019).”
What the sources say
- Partly supportedcites Ellis et al., 2019 sourceExperimental — accuracy not yet measured
The Discussion (p. 8) reports that the neural search framework scales to programs with very large branching factors, lending some support to the computational-capability point. Neither that passage nor the passages found by searching for noisy background knowledge and ∂ILP says that neural approaches handle noisy BK or identifies ∂ILP as an example. (LLM, conf=0.73)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Evans et al. (2021) apply the Apperception Engine to explain sequential data, such as rhythms and simple nursery tunes, image occlusion tasks, and sequence induction intelligence tests.”
What the sources say
- Supportedcites Evans et al., 2021 source
The Introduction lists rhythms and nursery tunes, sequence-induction intelligence tests, and occlusion problems among the domains tested with the Apperception Engine. Section 5.1.6 describes the occlusion tasks as visual scenes in which moving objects become hidden from view. (LLM, conf=0.93)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“PI shares the goal with feature or representation learning (Bengio et al., 2013) stream of research originating in the deep learning community (LeCun et al., 2015).”
What the sources say
- Supportedcites Bengio et al., 2013 source
The Introduction (p. 1) identifies feature learning with representation learning and describes its goal as learning data transformations that make useful information easier to extract. The citation supports the identification and goal of that research stream; the comparison with PI is the citing authors’ framing. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites LeCun et al., 2015 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although early work in ILP explored this form of learning (Sammut, 1981; Quinlan, 1990), it has been under-explored until recently (Lin et al., 2014; Cropper, 2019, 2020; Hocquette & Muggleton, 2020; Dumancic et al., 2021), mostly because of new techniques for PI.”
What the sources say
- Not matchedcites Sammut, 1981
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Partly supportedcites Quinlan, 1990 sourceExperimental — accuracy not yet measured
Section 4 describes FOIL learning definitions for one target relation at a time, and Section 7 says it uses other relations as background knowledge. That supports early work on multiple relational learning tasks, but the cited passages do not show FOIL retaining or transferring what it learned between tasks. The later claim about why the area was under-explored is attached to other citations, not Quinlan (1990). (LLM, conf=0.78)
- Not matchedcites Lin et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Reaching human-level AI is a desirable goal.
- Not matched
Every source the paper cites for this claim was checked and supports it.
In the paper
“Problog (De Raedt et al., 2007), a prominent member of this family, represents a minimal extension of Prolog that supports such stochastic execution.”
What the sources say
- Supportedcites De Raedt et al., 2007 source
The Introduction describes ProbLog as essentially Prolog with probabilities attached to clauses. It explains that queries succeed or fail in randomly sampled programs, supporting the characterization of a minimal probabilistic extension with stochastic execution. (LLM, conf=0.90)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“For this reason, ILP naturally supports lifelong (Silver et al., 2013), multi-task (Caruana, 1997), and transfer learning (Torrey & Shavlik, 2009), which are considered essential for human-like AI (Lake et al., 2016).”
What the sources say
- Not checked — no full text of the sourcecites Silver et al., 2013
- Supportedcites Caruana, 1997 source
Caruana is cited specifically for multi-task learning, not for the sentence’s separate claims about lifelong learning, transfer learning, or human-like AI. The paper’s Overview (§1.1) defines and describes multitask learning, so it supports that identification. (LLM, conf=0.93)
- Not matchedcites Torrey & Shavlik, 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Reaching human-level AI is a desirable goal.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“While StarAI is a growing field, inducing probabilistic logic programs has received little attention, with few notable exceptions (Bellodi & Riguzzi, 2015; De Raedt et al., 2015), as inference remains the main challenge.”
What the sources say
- Not matchedcites Bellodi & Riguzzi, 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites De Raedt et al., 2015
The citation is attached to “few notable exceptions,” and this paper is one: its Abstract describes a method for inducing logic programs in a probabilistic setting. The claim about inference being the main challenge appears after the citation and is not attributed to this source. (LLM, conf=0.91)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This program is semantically equivalent 33 to the previous one, but is shorter both in terms of the number of literals and clauses.”
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, grounding the permutation relation over the ASCII characters would require 128! facts.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although correct, this program is large and has 4 clauses and 12 literals.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most early attempts at PI were unsuccessful, and, as Table 4 shows, most systems do not support it.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Moreover, it is a single Prolog file, which makes it easy to download and use 40 .”
What the sources say
- Not matchedcites [40]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“it has a stable and easily available implementation with many options”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“TILDE learns from interpretations, instead of entailment as Aleph, and is an instance of top-down methodology.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Although TILDE learns normal programs, it requires them to be in the shape of a tree and does not support recursion.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Although TILDE learns normal programs, it requires them to be in the shape of a tree and does not support recursion.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Inductive logic programming (ILP) is a form of machine learning.”
- Also stated in: § 1. Introduction · p. 1 · plain
“Inductive logic programming (ILP) (Muggleton, 1991) is a form of ML.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1991 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Also stated in: § 1. Introduction · p. 1 · plain
None of the sources cited for this claim have been checked yet.
In the paper
“whereas most forms of ML use tables 1 to represent data (examples and hypotheses), ILP uses logic programs (sets of logical rules).”
What the sources say
- Not checked yetcites De Raedt, 2008 source
Checked before — its earlier verdict is held back until a new check runs.
- Not matchedcites Rockt¨ aschel and Riedel, 2017
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not checked yet
In the paper
“For instance, King et al. (1992) use ILP to model structure-activity relationships for drug design.”
What the sources say
- Not checked — no full text of the sourcecites King et al., 1992 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“ILP usually follows the closed world assumption (Reiter, 1977), so if anything is not explicitly true we assume it is false.”
What the sources say
- Not matchedcites Reiter, 1977
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Most ML algorithms are single-task learners and cannot reuse learned knowledge.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Whilst researching yeast-based functional genomics, the Robot Scientist became the first machine to independently discover new scientific knowledge (King et al., 2009).”
- Also stated in: § 7. Applications · p. 58 · plain
“Whilst researching yeast-based functional genomics, the Robot Scientist became the first machine to independently discover new scientific knowledge (King et al., 2009).”
What the sources say
- Not checked — no full text of the sourcecites King et al., 2009 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § 7. Applications · p. 58 · plain
In the paper
“This hypothesis corresponds to the quicksort algorithm (Hoare, 1961) and generalises to lists of arbitrary length and elements not seen in the training examples.”
What the sources say
- Not checked — no full text of the sourcecites Hoare, 1961 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This scenario shows that ILP is a form of program synthesis (Shapiro, 1983), where the goal is to automatically build executable programs.”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Because they are closely related to relational databases, logic programs naturally support relational data such as graphs.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Because of the symbolic nature of logic programs, ILP can reason about hypotheses, which allows it to learn optimal programs, such as minimal time-complexity programs (Cropper & Muggleton, 2019) and secure access control policies (Law et al., 2020).”
What the sources say
- Not matchedcites Cropper & Muggleton, 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Law et al., 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Unrestricted, the hypothesis space is infinite, so it is vital to restrict it to make the search feasible.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The representation determines the learning setting which in turn defines what it means for a program to solve the ILP problem.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“As Srinivasan et al. (1994) state, 'There is more to scientific theory formulation than data fitting. To be acceptable, a theory must be understandable and open to critical analysis' .”
What the sources say
- Not matchedcites Srinivasan et al., 1994
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Not matched
In the paper
“Moreover, because induced hypotheses have the same language as the BK, they can be stored in the BK, making transfer learning trivial (Lin et al., 2014).”
What the sources say
- Not matchedcites Lin et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“Some languages support non-monotonic reasoning, such as answer set programming (Gebser et al., 2012).”
What the sources say
- Not matchedcites Gebser et al., 2012
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“ILP represents data as logic programs.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, it is trivial to define a summation relation over the infinite set of natural numbers ( add(A,B,C):C = A+B ).”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“For instance, the Robot Scientist (King et al., 2004) is a system that uses ILP to generate hypotheses to explain data and can also automatically devise experiments to test the hypotheses, physically run the experiments, interpret the results, and then repeat the cycle.”
What the sources say
- Not checked — no full text of the sourcecites King et al., 2004 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using logic programs to represent data allows ILP to learn with complex relational information and for easy integration of expert knowledge.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Because of logic's similarity to natural language, logic programs can be easily read by humans, which is crucial for explainable AI 5 .”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Building an ILP system (Figure 1) requires making several choices or assumptions.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“For instance, although AlphaGo (Silver et al., 2016) has super-human Go ability, it cannot reuse this knowledge to play other games, nor the same game with a slightly different board.”
What the sources say
- Not checked — no full text of the sourcecites Silver et al., 2016 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“By contrast, tabled-based ML approaches are mostly restricted to finite data and cannot represent this information.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There are, however, many logic programming languages, each with strengths and weaknesses.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“if we train a neural system to add numbers with 10 digits, it can generalise to numbers with 20 digits, but when tested on numbers with 100 digits, the predictive accuracy drastically decreases (Reed & de Freitas, 2016; Kaiser & Sutskever, 2016).”
What the sources say
- Not matchedcites Reed & de Freitas, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Kaiser & Sutskever, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“For instance, when inducing solutions to a set of string transformation tasks, such as those in Scenario 2, Lin et al. (2014) show that an ILP system can automatically identify easier problems to solve, learn programs for them, and then reuse the learned programs to help learn programs for more difficult problems.”
What the sources say
- Not matchedcites Lin et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Choosing a suitable representation language is crucial in determining which problems a system can solve.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
In the paper
“However, if we follow Mitchell's (1997) definition of ML 8 then ILP is no different from other ML approaches: it improves given more examples.”
What the sources say
- Not matchedcites Mitchell, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Choosing an appropriate language bias is necessary for efficient learning and is a major challenge.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Datalog is, however, sufficient for the happy Scenario because structured terms are unnecessary.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“By contrast, definite programs with function symbols have the expressive power of Turing machines and are consequently undecidable (T¨ arnlund, 1977).”
What the sources say
- Not matchedcites T¨ arnlund, 1977
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“ILP is in the symbolic learning category.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“However, as Domingos (2015) points out, there are generally five areas of ML: symbolists, connectionists, Bayesian, analogisers, and evolutionists.”
What the sources say
- Not matchedcites Domingos, 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unlike Prolog, Datalog is purely declarative.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, the clause p ( a ) ∨ p ( b ) cannot be expressed in Horn logic because it has two positive literals.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Most Prolog implementations (Wielemaker et al., 2012; Costa et al., 2012) allow extra-logical features, such as cuts.”
What the sources say
- Not matchedcites Wielemaker et al., 2012
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Costa et al., 2012
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, most work in ILP focuses on fragments of clausal logic, such as Horn programs: clauses with at most one positive literal.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Turing can be seen as one of the first symbolist, as he proposed using a logical representation to build thinking machines (Turing, 1950; Muggleton, 1994a).”
What the sources say
- Not checked — no full text of the sourcecites Turing, 1950 source
- Not matchedcites Muggleton, 1994a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Recognising the limitations of table-based representations, Banerji (1964) proposed using predicate logic as a representation language for learning.”
What the sources say
- Not matchedcites Banerji, 1964
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“ILP as a field was founded by Muggleton (1991), who stated that it lies at the intersection of ML and knowledge”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1991 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Prolog is not purely declarative because of constructs like cut, which means that a procedural reading of a Prolog program is needed to understand it.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Other notable contributions include inverse resolution (Muggleton & Buntine, 1988), which was also one of the earliest approaches at predicate invention.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton & Buntine, 1988 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Meta-level approaches often delegate the search for a hypothesis to an off-the-shelf solver (Corapi et al., 2011; Muggleton et al., 2014; Law et al., 2014; Kaminski et al., 2018; Evans et al., 2021; Cropper & Morel, 2021) after which the meta-level solution is translated back to a standard solution for the ILP problem.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Muggleton et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Law et al., 2014 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In other words, the order of clauses in a Prolog program has a major influence on its execution and results.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, this decidability comes at the cost of expressivity as Datalog is not Turing complete.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The traditional way to categorise approaches is whether they use a top-down or bottomup search, where generality orders the search space 7 .”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Other notable work includes Vera (1975) on induction algorithms for predicate calculus and Sammut's (1981) MARVIN system, one of the first to learn executable programs.”
What the sources say
- Not matchedcites Vera, 1975
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“As with all ML techniques, ILP restricts the hypothesis space by enforcing an inductive bias (Mitchell, 1997).”
What the sources say
- Not matchedcites Mitchell, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the list manipulation programs from previous sections cannot (easily) be expressed in Datalog 9 .”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Some approaches combine the two (Muggleton, 1995; Srinivasan, 2001; Cropper, 2022).”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1995 source
- Not matchedcites Srinivasan, 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Cropper, 2022
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“McCarthy (1959) made the first comprehensive proposal for the use of logic in AI with his advice seeker .”
What the sources say
- Not matchedcites McCarthy, 1959
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Shapiro's (1983) work on inducing Prolog programs made major contributions to ILP, including the concepts of backtracking and refinement operators.”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Other notable work includes Vera (1975) on induction algorithms for predicate calculus and Sammut's (1981) MARVIN system, one of the first to learn executable programs.”
What the sources say
- Not matchedcites Sammut, 1981
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Robinson (1965) showed that a single rule of inference (the resolution principle) is both sound and refutation complete for clausal logic.”
What the sources say
- Not matchedcites Robinson (1965)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Plotkin's (1971) work on subsumption and least general generalisation has influenced nearly all of ILP, especially theory.”
What the sources say
- Not matchedcites Plotkin, 1971
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Michalski's (1969) work on the AQ algorithm, which induces rules using a set covering algorithm, has greatly influenced many ILP systems.”
What the sources say
- Not checked — no full text of the sourcecites Michalski, 1969 source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In addition, ASP programs support rules that are not available in Prolog, such as choice rules and weak and hard constraints.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“According to De Raedt (1997), there are three main ILP learning settings: learning from entailment (LFE), interpretations (LFI), and satisfiability (LFS).”
What the sources say
- Not matchedcites De Raedt (1997)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For instance, to learn a definition of a recursive concept, the hypothesis needs to capture at least the base and recursive case.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: Often, a single clause is insufficient to describe a target concept.
In the paper
“An inductive bias is essential and all ML approaches impose an inductive bias (Mitchell, 1997).”
What the sources say
- Not matchedcites Mitchell, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Building an ILP system requires making several choices or assumptions, which are part of the inductive bias of a learner.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“ILP approaches that learn normal logic programs can further be characterised by their semantics, such as whether they are based on completion (Clark, 1977), well-founded (Gelder et al., 1991), or stable model (answer set) (Gelfond & Lifschitz, 1988) semantics.”
What the sources say
- Not matchedcites Clark, 1977
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Gelder et al., 1991 source
- Not checked — no full text of the sourcecites Gelfond & Lifschitz, 1988
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“As providing a complete interpretation might be unfeasible in many cases, many ILP systems focus on partial interpretations (De Raedt, 1997).”
What the sources say
- Not matchedcites De Raedt, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Most ASP solvers (Gebser et al., 2012), in principle, always terminate (unlike Prolog query evaluation, which may lead to an infinite loop).”
What the sources say
- Not matchedcites Gebser et al., 2012
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A generality order helps structure the search over the hypothesis space by reasoning about the relative properties of two programs.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: A key concept in ILP is the generality order over hypotheses (logic programs).
In the paper
“When learning Prolog programs with NAF, the programs must be stratified; otherwise, the learned program may loop under certain queries (Law et al., 2018).”
What the sources say
- Not matchedcites Law et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“There are many benefits to learning ASP programs (Otero, 2001; Law et al., 2014).”
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
In the paper
“Some systems, such as Progol (Muggleton, 1995), allow for clauses as examples.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1995 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These relations are general and hold for arbitrary numbers and we do not need to precompute all the logical consequences of the definitions, which is impossible because there are infinitely many.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similar to Datalog, an answer set program is purely declarative.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By contrast, table-based ML approaches are restricted to finite propositional data. For instance, it is impossible to use the greater than relation over the set of natural numbers in a decision tree learner because it would require an infinite feature table.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Inoue et al. (2013) represent knowledge as a causal graph and use constraints to denote impossible connections between nodes.”
What the sources say
- Not matchedcites Inoue et al., 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“Most approaches reason about the generality of programs syntactically through θ -subsumption (or subsumption for short) (Plotkin, 1971).”
What the sources say
- Not matchedcites Plotkin, 1971
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The two main learning settings are LFE and LFI (Section 3).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“For instance, the default cost function in Aleph (Srinivasan, 2001) is coverage , defined as the number of positive examples entailed subtracted by the number of negative examples entailed by the hypothesis.”
What the sources say
- Not matchedcites Srinivasan, 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Although some systems learn propositional programs, such as Duce (Muggleton, 1987), most learn first-order (or higher-order) programs.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1987
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These relations hold for lists of any length and any type.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“The logic of definite clauses with negation as failure (NAF) (Clark, 1977) is nonmonotonic, which brings us to the special class of normal logic programs , which take the following form:”
What the sources say
- Not matchedcites Clark, 1977
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Most systems, however, learn from sets of facts, so this dimension of comparison is not useful.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Systems that focus on program synthesis (Shapiro, 1983; Bratko, 1999; Ahlgren & Yuen, 2013; Cropper & Muggleton, 2016, 2019; Cropper & Morel, 2021) tend to induce definite programs, typically as Prolog programs.”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
- Not matchedcites Bratko, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Ahlgren & Yuen, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Definite programs are monotonic because anything that could be deduced before a (definite) clause is added to it can still be deduced after it is added.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Too many relations (assuming that they can appear in a hypothesis) is often a problem because the size of the hypothesis space is a function of the size of the BK.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“For instance, HYPER (Bratko, 1999) searches a tree in which the nodes correspond to hypotheses. Each child of a hypothesis in the tree is more specific than or equal to its predecessor in terms of theta-subsumption, i.e. a hypothesis can only entail a subset of the examples entailed by its parent.”
What the sources say
- Not matchedcites Bratko, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In contrast to other forms of bias in ILP, such as modes or grammars, metarules are themselves logical statements, which allows us to reason about them.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unrestricted, the hypothesis space is infinite, so it is important to restrict it to make the search feasible.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Likewise, if a clause entails a negative example, then there is no need to explore any of its generalisations because they will also entail the example.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Providing a recall is a hint to a system to ignore certain hypotheses.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A generality relation imposes an order over the hypothesis space.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim.
In the paper
“The Blumer bound (Blumer et al., 1987) (the bound is a reformulation of Lemma 2.1) helps explain this trade-off. This bound states that given two hypothesis spaces, searching the smaller space will result in fewer errors compared to the larger space, assuming that the target hypothesis is in both spaces.”
What the sources say
- Not checked — no full text of the sourcecites Blumer et al., 1987 source
plaindirect- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: The target hypothesis is in both hypothesis spaces.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Depending on the specific system, modes can also support the introduction of constant symbols.”
plainconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Bottom-up algorithms start with the examples and generalise them (Muggleton, 1987; Muggleton & Buntine, 1988; Muggleton & Feng, 1990; Muggleton et al., 2009; Inoue et al., 2014).”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1987
- Not checked — no full text of the sourcecites Muggleton & Buntine, 1988 source
- Not checked — no full text of the sourcecites Muggleton & Feng, 1990
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Different systems use mode declarations in slightly different ways.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Metarules are second-order rules which define the structure of learnable programs which in turn defines the hypothesis space.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There are two traditional search methods: bottom-up and top-down .”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Metarules 17 are a popular form of syntactic bias and are used by many systems (De Raedt & Bruynooghe, 1992; Flener, 1996; Kietz & Wrobel, 1992; Wang et al., 2014; Muggleton et al., 2015; Cropper & Muggleton, 2016; Kaminski et al., 2018; Evans & Grefenstette, 2018; Bain & Srinivasan, 2018).”
What the sources say
- Not matchedcites De Raedt & Bruynooghe, 1992
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Flener, 1996
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Kietz & Wrobel, 1992
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If a user does not have such knowledge, then it can be very difficult to determine suitable mode declarations.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“To introduce RLGG, we start by introducing Plotkin's (1971) notion of least-general generalisation (LGG), which tells us how to generalise two clauses.”
What the sources say
- Not matchedcites Plotkin, 1971
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Progol and Aleph use mode declarations with input/output argument types because they induce Prolog programs, where the order of literals in a rule matters.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, if a clause does not entail a positive example, then there is no need to explore any of its specialisations because it is logically impossible for them to entail the example.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Mode declarations are expressive enough to enforce a strong bias to significantly prune the hypothesis space.”
boosteddirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A benefit of metarules is that they require little knowledge of the BK and a user does not need to provide recall values, types, or specify input/output arguments.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The difficulty is finding the balance of having enough BK to solve a problem, but not too much that a system becomes overwhelmed.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“By contrast, ILASP induces ASP programs, where the order of literals in a rule does not matter, so ILASP does not use input/output arguments.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“If a hypothesis is considered that does not entail all the positive examples, it is immediately discarded because it can never be refined into a complete hypothesis.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“For instance, Golem (Muggleton & Feng, 1990) generalises pairs of examples based on relative least-general generalisation (RLGG) (Buntine, 1988).”
What the sources say
- Not checked — no full text of the sourcecites Muggleton & Feng, 1990
- Not checked — no full text of the sourcecites Buntine, 1988 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These methods rely on notions of generality, where one program is more general or more specific than another (Section 2.4).”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite this preliminary work, deciding which metarules to use for a given problem is still a major challenge, which future work must address.”
- Also stated in: § 4.4.3 Discussion · p. 27 · plain
“However, as previously mentioned, the major downside with metarules is determining which metarules to use for an arbitrary learning task.”
- Also stated in: § 4.4.3 Discussion · p. 27 · plain
“Although there is some preliminary work in identifying universal sets of metarules (Cropper & Muggleton, 2014; Tourret & Cropper, 2019; Cropper & Tourret, 2020), deciding which metarules to use for a given problem is a major challenge, which future work must address.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: There is little work determining which metarules to use for a given learning task.
- Rests on an assumption: These approaches assume suitable metarules as input or use metarules without any theoretical guarantees.
- Also stated in: § 4.4.3 Discussion · p. 27 · plain
None of the sources cited for this claim have been checked yet.
In the paper
“ASPAL (Corapi et al., 2011), ILASP (Law et al., 2014), HEXMIL (Kaminski et al., 2018), and the Apperception Engine (Evans et al., 2021) translate an ILP problem into an ASP problem and use powerful ASP solvers to find a model of the problem - note that these systems all employ very different algorithms.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Law et al., 2014 source
- Not matchedcites Kaminski et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The main advantages of top-down approaches are that they can more easily learn recursive programs and textually minimal programs.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Bottom-up approaches can be seen as being dataor example-driven .”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The main advantages of top-down approaches are that they can more easily learn recursive programs and textually minimal programs.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Progol is one of the most important systems and has inspired many other approaches (Srinivasan, 2001; Ray, 2009; Ahlgren & Yuen, 2013), including Aleph, which we cover in detail in Section 6.1.”
What the sources say
- Not matchedcites Srinivasan, 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Ray, 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Ahlgren & Yuen, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Law et al. (2020) also provide an overview of conflict-driven ILP, which the systems ILASP3 (Law, 2018) and Popper (Cropper & Morel, 2021) adopt.”
What the sources say
- Not matchedcites Law et al., 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There is no agreed-upon definition for what meta-level ILP means, but most approaches encode the ILP problem as a meta-level logic program, i.e. a program that reasons about programs.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“ASPAL then uses an ASP system to find a subset of the rules that cover all the positive but none of the negative examples.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The major advantage of these approaches is that they are typically very fast.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The major disadvantage is that they can be prohibitively inefficient because they can generate many hypotheses that do not cover even a single positive example.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“ASPAL uses an ASP optimisation statement to find the hypothesis with the fewest literals.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The use of a bottom clause bounds the search from above (the empty set) and below (the bottom clause).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Progol is, however, slightly confusing because it is a top-down system but it first uses a bottom-up approach to bound the search space.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The A* search strategy employed by Progol can easily be replaced by alternative search algorithms, such as stochastic search (Muggleton & Tamaddoni-Nezhad, 2008).”
What the sources say
- Not checked — no full text of the sourcecites Muggleton & Tamaddoni-Nezhad, 2008 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Buntine's (1988) notion of relative least-general generalisation computes a LGG of two examples relative to the BK (assumed to be a set of facts):”
What the sources say
- Not checked — no full text of the sourcecites Buntine, 1988 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, TILDE keeps specialising every clause which leads to improvement (i.e., a clause covers fewer negative examples).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Given two clauses, the LGG operator returns the most specific single clause that is more general than both of them.”
What the sources say
- Not matchedcites Plotkin, 1971
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“For instance, ASPAL (Corapi et al., 2011) translates an ILP problem into a meta-level ASP program which describes every example and every possible rule in the hypothesis space (defined by mode declarations).”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this way, Progol is a top-down approach.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this way, Progol is a bottom-up approach because it starts with a bottom clause and tries to generalise it.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, as Progol illustrates, there is not necessarily clear distinctions between top-down , bottom-up , and meta-level approaches.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There is no agreed-upon definition for what meta-level ILP means, but most approaches encode the ILP problem as a meta-level logic program, i.e. a program that reasons about programs.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“However, as Bratko (1999) points out, there are several disadvantages of bottom-up approaches, such as (i) they typically use unnecessarily long hypotheses with many clauses, (ii) it is difficult for them to learn recursive hypotheses and multiple predicates simultaneously, and (iii) they do not easily support predicate invention.”
What the sources say
- Not matchedcites Bratko, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The different search methods discussed above have different advantages and disadvantages, and there is no 'best' approach.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Metaopt maintains a cost during the hypothesis search and uses this cost to prune the hypothesis space.”
What the sources say
- Not matchedcites Cropper & Muggleton, 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“ILASP and ∂ ILP support predicate invention, but only a restricted form. See Section 5.5 for an explanation.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“FOIL, Progol, and XHAIL can learn recursive programs when given sufficient examples. See Section 5.4 for an explanation.”
plainconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“For instance, Metagol does not support noise and thus has the value no in the noise column, but there is an extension (Muggleton et al., 2018) that samples examples to mitigate the issue of misclassified examples.”
What the sources say
- Not matchedcites Muggleton et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“For instance, Metagol does not support noise and thus has the value no in the noise column, but there is an extension (Muggleton et al., 2018) that samples examples to mitigate the issue of misclassified examples.”
What the sources say
- Not matchedcites Muggleton et al., 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Most systems that use a set covering loop naturally support noise handling.”
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The problem definitions from Section 3 are too strong to account for noisy (incorrectly labelled) examples because they expect a hypothesis that entails all of the positive and none of the negative examples.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim.
In the paper
“Many approaches also precompute every possible rule in a hypothesis (Corapi et al., 2011; Law et al., 2014), so struggle to learn programs with large rules, although preliminary work tries to address this issue (Cropper & Dumanˇ ci´ c, 2020).”
What the sources say
- Not matchedcites Cropper & Dumanˇ ci´ c, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, most systems assume that the BK is perfect, i.e. that atoms are true or false, and there is no room for uncertainty.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There are often multiple (sometimes infinite) hypotheses that solve the ILP problem (or have the same training error).”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Handling imperfect BK is an under-explored topic in ILP.”
plain- Asserted: passes — The authors put it forward as true.
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In general, handling noisy examples is a wellstudied topic in ILP.”
boosted- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“One of the key appealing features of ∂ ILP is that it takes a differentiable approach to ILP and can be given fuzzy or ambiguous data.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, because a system learns only a single clause per example 30 , this covering approach requires examples of both the base and inductive cases, which means that such systems struggle to learn recursive programs, especially from small numbers of examples.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, in this approach, the numeric computation is performed when grounding the inputs, so the grounding must be finite, which makes it impractical.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
In the paper
“The authors show that this approach allows a user to optimise domain-specific performance metrics on real-world datasets, such as access control policies.”
What the sources say
- Not matchedcites Law et al., 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For instance, to learn the quicksort algorithm, a learner needs to be able to partition the list given a pivot element and append two lists.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“For instance, ILASP (Law et al., 2014) can represent real numbers as strings and can delegate reasoning to Python (via Clingo's scripting feature).”
What the sources say
- Not checked — no full text of the sourcecites Law et al., 2014 source
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“This finite grounding restriction is often achieved by enforcing syntactic restrictions on the programs, such as finitely-ground programs Calimeri et al. (2008).”
What the sources say
- Not checked — no full text of the sourcecites Calimeri et al. (2008) source
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A classical example of PI is learning the definition of grandparent from only the background relations mother and father .”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The grounding bottleneck is especially a problem when reasoning about real numbers 29 .”
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, ∂ ILP is an ILP system based on a neural network, but it only works on BK in the form of a finite set of ground atoms.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This assumption may not always hold.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“For instance, FastLAS (Law et al., 2020) follows this idea and takes as input a custom scoring function and computes an optimal solution for the given scoring function.”
What the sources say
- Not matchedcites Law et al., 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Most systems assume that the given BK is suitable to induce a solution.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, the chain metarule ( P ( A,B ) ← Q ( A,C ) , R ( C, B )) allows Metagol to induce programs 31 such as:”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The power of recursion is that an infinite number of computations can be described by a finite recursive program (Wirth, 1985).”
What the sources say
- Not matchedcites Wirth, 1985
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The key idea of MIL is to use metarules (Section 4.4.2) to restrict the form of inducible programs and thus the hypothesis space.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If partition and append are not provided in BK, the learner would need to invent them.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Aleph is one of the most popular ILP systems because (i) it has a stable and easily available implementation with many options, and (ii) it has good empirical performance.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: Aleph has good empirical performance.
In the paper
“Moreover, it is a single Prolog file, which makes it easy to download and use 40 .”
What the sources say
- Not matchedcites [40]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The key thing to understand is that Aleph's search is bounded from above (the most general clause) and below (the most specific clause).”
- Also stated in: § 6.1.5 Discussion · p. 47 · plain
“Aleph bounds the hypothesis space from above (the most general hypothesis) and below (the most specific hypothesis).”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § 6.1.5 Discussion · p. 47 · plain
In the paper
“Aleph is based on Progol.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1995 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“As Kramer (1995) points out, PI is difficult for at least three reasons:”
What the sources say
- Not matchedcites Kramer, 1995
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The invented interpretations compress the given examples and invent useful predicates by capturing regularities in the data 36 .”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The purpose of constructing a bottom clause is to bound the search in step 3.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In general, a bottom clause can have infinite cardinality.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Aleph is based on inverse entailment (Muggleton, 1995) and uses bottom clause construction to restrict the hypothesis space.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1995 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“To learn this program, Metagol ho invents the predicate symbol droplasts1 , which is used twice in the program: once as term in the literal map(A,B,droplasts1) and once as a predicate symbol in the literal droplasts1(A,B) .”
plaindirectSingle case- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Finally, Metagol uses a Prolog meta-interpreter to construct a proof of a set of examples and extracts a program from the proof.”
What the sources say
- Not checked — no full text of the sourcecites Cropper & Muggleton, 2016 source
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Given suitable examples, metarules, and BK, Metagol ho learns the program:”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The aforementioned techniques for PI are aimed at single-task problems.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This program is similar to the aforementioned droplasts program, but additionally reuses the invented predicate symbol ddroplasts1 in the literal ddroplasts1(C,B) .”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Tasks 4, 5, and 16 cannot be solved using an independent learning approach, but can when using a dependent learning approach.”
What the sources say
- Not matchedcites Lin et al. (2014)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In other words, Aleph only considers clauses that are generalisations of the bottom clause, which must all entail the example.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Any clause that is not more general than the bottom clause cannot entail e so can be ignored.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“ASPAL is a meta-level system that uses an ASP solver to solve the ILP problem, which has influenced much subsequent work, notably ILASP.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The invented symbol inv can be interpreted as parent .”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“There are many PI techniques.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given insufficient metarules, the hypothesis space might be too small as to exclude a good hypothesis.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note the usage of the cut ( ! ) operator, which is essential to ensure that only one branch of the decision tree holds for each example.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The answer sets of this meta-level program are solutions to the ILP problem.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“predicting mutagenic activity of molecules and identifying structural alerts for the causes of chemical cancers (Srinivasan et al., 1997, 1996)”
What the sources say
- Not matchedcites Srinivasan et al., 1997, 1996
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The learning setup of TILDE is different from other ILP systems in the sense that it closely mimics the standard classification setup from machine learning.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“ASPAL (Corapi et al., 2011) was one of the first meta-level ILP systems, which directly influenced other ILP systems, notably ILASP.”
What the sources say
- Not matchedcites Corapi et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“inferring missing pathways in protein signalling networks (Inoue et al., 2013)”
What the sources say
- Not matchedcites Inoue et al., 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given too many metarules, the hypothesis space might be so large that the search is intractable.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Due to the expressivity of logic programs as a representation language, ILP systems have found successful applications in software design.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“To learn optimal programs, Metagol enforces a bound on the program size (the number of metasubs).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These parameters can greatly influence learning performance.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TILDE's stepwise refinement keeps the number of inequality tests tractable.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Metarules are fundamental to Metagol.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, TILDE inherits the limitations of top-down systems, such as generating many needless candidates.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It also learns optimal programs by employing ASP optimisation constraints.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If a problem contains predicates of arities greater than two, then Metagol is unsuitable.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TILDE behaves almost the same as C4.5 limited to binary attributes, meaning that it uses the same heuristics and pruning techniques.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even for experts, it is non-trivial to find a suitable set of parameters for a problem.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“What TILDE does differently is the generation of candidates splits. Whereas C4.5 generates candidates as attribute-value pairs (or value inequalities in case of continuous attributes), TILDE uses conjunctions of literals.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The Robot Scientist uses logical BK to represent the relationships between protein-coding sequences, enzymes, and metabolites in a pathway.”
What the sources say
- Not checked — no full text of the sourcecites King et al., 2009 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The Robot Scientist uses ILP to automatically generate hypotheses to explain data and then devises experiments to test hypotheses, run the experiments, interpret the results, and then repeat the cycle (King et al., 2004).”
What the sources say
- Not checked — no full text of the sourcecites King et al., 2004 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The introduction of a literal with the number of components predicate is only helpful if it is introduced together with the inequality related to the second argument of the literal.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Metagol uses iterative deepening to search for hypotheses.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For some tasks, such as string transformations, it is straightforward to choose a suitable set of metarules because one already knows the general form of hypotheses.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The last condition ensures that a hypothesis is an instance of the given metarules.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“There is much interest in this topic, largely due to success in synthesising programs for end-user problems, such as string transformations in Microsoft Excel (Gulwani, 2011).”
What the sources say
- Not matchedcites Gulwani, 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Another successful application of ILP is in data curation and transformation, which is again largely because ILP can learn executable programs.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“and Antanas et al. (2015) recognise graspable points on objects through relational representations of objects.”
What the sources say
- Not matchedcites Antanas et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Cropper et al. (2020b) introduce the ILP problem of inductive general game playing : the problem of inducing game rules from observations, such as Checkers , Sokoban , and Connect Four .”
What the sources say
- Not matchedcites Cropper et al. (2020b)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Legras et al. (2018) show that Aleph and TILDE can outperform an SVM learner in the game of Bridge.”
What the sources say
- Not checked — no full text of the sourcecites Legras et al. (2018) source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Universal induction methods, such as Solomonoff induction (Solomonoff, 1964a, 1964b) and Levin search (Levin, 1973) are forms of program synthesis.”
What the sources say
- Not matchedcites Solomonoff, 1964a, 1964b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Levin, 1973
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Bain (1994) studies inducing rules to determine the legality of moves in the chess KRK (king-rook-king) endgame.”
What the sources say
- Not matchedcites Bain (1994)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Other transformation tasks include extracting values from semi-structured data (e.g. XML files or medical records), extracting relations from ecological papers, and spreadsheet manipulation (Cropper et al., 2015).”
What the sources say
- Not matchedcites Cropper et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“By contrast, the major challenge in ML (and thus ILP) is learning hypotheses that generalise to unseen examples.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“For instance, an ILP system can trivially construct the bottom clause (Muggleton, 1995) for each example.”
What the sources say
- Not checked — no full text of the sourcecites Muggleton, 1995 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Inducing game rules has a long history in ILP, where chess has often been the focus (Goodacre, 1996; Morales, 1996; Muggleton et al., 2009).”
What the sources say
- Not matchedcites Goodacre, 1996
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Morales, 1996 source
- Not matchedcites Muggleton et al., 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“However, universal methods are impractical because they learn only from examples and, as Mitchell (1997) points out, bias-free learning is futile.”
What the sources say
- Not matchedcites Mitchell (1997)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The two major 46 differences between ML and PL approaches are (i) the generality of solutions (synthesised programs) and (ii) noise handling.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ILP is well-suited for addressing such tasks for three reasons (i) it is based on an expressive formal language that can capture/respect the syntax and semantics of the natural language”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Rests on an assumption: Many natural language processing tasks require an understanding of the syntax and semantics of the language.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When given no BK, and thus no inductive bias, inductive program synthesis methods are equivalent to universal induction methods.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“and software specification recovery from execution behaviour (Cohen, 1994b, 1995a).”
What the sources say
- Not matchedcites Cohen, 1994b, 1995a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“For instance, The Robot Engineer (Sammut et al., 2015) uses ILP to design tools for robots and even complete robots, which are tests in simulations and real-world environments.”
What the sources say
- Not checked — no full text of the sourcecites Sammut et al., 2015
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Castillo and Wrobel (2003) uses a top-down ILP system and active learning to induce a rule for when a square is safe in the game minesweeper.”
What the sources say
- Not checked — no full text of the sourcecites Castillo and Wrobel (2003)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Similar to universal induction methods, inductive program synthesis systems learn programs from incomplete specifications, typically input/output examples.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Universal induction methods take only examples as input and are inefficient at building programs.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Similarly, noise handling is a major problem in ML, yet is rarely considered in the PL literature.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Indeed, it is often trivial to learn an overly specific solution for a given problem.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Similarly, simple electronic circuits can be constructed from the examples of the target behaviour and the physics of basic electrical components (Grobelnik, 1992)”
What the sources say
- Not matchedcites Grobelnik, 1992
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Because ILP induces programs, it is also a form of program synthesis (Shapiro, 1983), where the goal is to build a program from a specification.”
What the sources say
- Not checked — no full text of the sourcecites Shapiro, 1983 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Interest in inductive program synthesis has grown recently, partly due to applications in real-world problems, such as end-user programming (Gulwani, 2011).”
What the sources say
- Not matchedcites Gulwani, 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Law et al. (2014) uses ILASP to induce the rules for Sudoku and show that this more expressive formalism allows for game rules to be expressed more compactly.”
What the sources say
- Not checked — no full text of the sourcecites Law et al. (2014) source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Learning from interpretation transitions (LFIT) (Inoue et al., 2014) automatically constructs a model of the dynamics of a system from the observation of its state transitions”
What the sources say
- Not matchedcites Inoue et al., 2014
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Given time-series data of discrete gene expression, it can learn gene interactions, thus allowing to explain and predict states changes over time (Ribeiro et al., 2020).”
What the sources say
- Not checked — no full text of the sourcecites Ribeiro et al., 2020
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“In contrast to universal induction methods, inductive program synthesis systems use BK, and are thus less general than universal methods, but are more practical because the BK is a form of inductive bias (Mitchell, 1997) which restricts the hypothesis space.”
What the sources say
- Not matchedcites Mitchell, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly to the previous category, robotics applications often require incorporating domain knowledge or imposing certain requirements on the learnt programs.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Consequently, the notion of entailment loses its crispness and needs to be interpreted in the continuous spectrum.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The learning task is then to fit the valuations such that positive examples have high valuations and the valuations of negative examples are low, for which any numerical optimisation techniques can be used.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Although there is some work on mode learning (McCreath & Sharma, 1995; Ferilli et al., 2004; Picado et al., 2017) and work on identifying suitable metarules (Cropper & Tourret, 2020), this area of research is largely under-researched.”
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The central goal of representation learning coincides with the one behind PI: improving learning performance by changing the representation of a problem.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An alternative interpretation of this statement is that 1% of executions of the probabilistic program would observe an earthquake.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One reason is that ILP systems are often only designed as prototypes and are often not well-engineered or maintained.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Problog introduces two types of probabilistic choices: probabilistic facts and annotated disjunctions.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“As introduced in Section 5.5, predicate invention (PI) - changing the representation of a problem by introducing new predicates symbols defined in terms of provided predicates - is one of the major open challenges in ILP.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A fact entailed by c is said to be entailed with valuation w c ; a valuation of a fact is then the sum of valuations of all c that entail it.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, to leverage these techniques, ILP needs to be framed as a problem over a fixed set of variables, which is perhaps unnatural given that hypothesis spaces in ILP are combinatorial and essentially infinite.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, PI is still difficult and there are many challenges to overcome.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Rests on an assumption: Reaching human-level AI is a desirable goal.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“While integrating ILP and program synthesis with neural networks is a proliferating area, relatively few approaches tackle the ILP problem.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“They take the form of logical facts labeled with a probability p and represent a Boolean random variable that is true with probability p and false with probability 1 -p .”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These techniques make the hypothesis space finite by limiting its complexity and consequently only learn syntactically simple programs (e.g., the ones up to two literals and two clauses).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If a user can provide suitable metarules, then Metagol is extremely efficient.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“How often a fact is deemed true or false is guided by the stated probability.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“That is, every member c of the hypothesis space is associated with valuation w c which indicate the confidence that the entailments of c are correct.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although new methods for PI (Section 5.5) can invent high-level concepts, they are not yet sufficiently powerful enough to perform well on the IGGP dataset.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
- Rests on an assumption: Reaching human-level AI is a desirable goal.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The main challenges in transferring the ideas from representation learning to PI are their different operating principles.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This difficulty of use is compounded by ILP systems often using many different biases or even different syntax for the same biases.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In contrast to deterministic logic programs in which a fact is always true if so stated, the Problog engine determines the truth assignment of a probabilistic fact when it encounters it during SLD resolution, the main execution principle of logic programs.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Annotated disjunctions allow for multiple literals in the head, but only one of the head literals can be true at a time.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Probabilistic facts are the most basic stochastic unit in Problog.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Additionally, integrating neural networks into ILP would make it possible for ILP to deal with unstructured data, such as images and sound, and noise associated with unstructured data.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Whereas probabilistic facts introduce non-deterministic behaviour on the level of facts, annotated disjunctions introduce non-determinism on the level of clauses.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“What makes this research direction interesting is that the techniques are based on numerical optimisation and, if successful, could learn programs without combinatorial search, which is the core reason why ILP is a difficult problem.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The successes of deep learning on various tasks have prompted researchers to investigate whether these techniques can be used to solve the ILP problem.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Though StarAI frameworks allow for incorrect BK, they add another level of complexity to learning: besides identifying the right program (also called structure in StarAI), the learning task also consists of learning the corresponding probabilities of probabilistic choices (also called parameters).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Although too much irrelevant BK is detrimental to learning performance (Srinivasan et al., 1995, 2003), there is almost no work in ILP on trying to identify relevant BK.”
What the sources say
- Not matchedcites Srinivasan et al., 1995, 2003
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Without efficient relevancy methods, it is unclear how lifelong learning can be achieved.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: Reaching human-level AI is a desirable goal.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, much real-world data, such as images and speech, cannot easily be translated into a symbolic form.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By the inherent nature of induction, induced programs are not guaranteed to be correct (i.e. are expected to be noisy), yet they are the building blocks for subsequent induction.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Explainability is one of the claimed advantages of a symbolic representation.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most ILP systems require data in perfect symbolic form.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
The paper relies on this without support.
Most forms of machine learning learn functions.
“Moreover, whereas most forms of ML learn functions, ILP learns relations.”
The paper relies on this without support.
Most ML approaches rely on statistical inference.
“Most ML approaches rely on statistical inference.”
The paper relies on this without support.
ILP relies on logical inference and uses techniques from automated reasoning and knowledge representation.
“By contrast, ILP relies on logical inference and uses techniques from automated reasoning and knowledge representation .”
The paper relies on this without support.
Prolog is a Turing-complete logic programming language.
“For instance, Prolog is a Turing-complete logic programming language.”
The paper relies on this without support.
Datalog is a syntactical subset of Prolog that sacrifices features and expressivity (it is not Turing-complete) to gain efficiency and decidability.
“Datalog is a syntactical subset of Prolog that sacrifices features (such as data structures) and expressivity (it is not Turingcomplete) to gain efficiency and decidability.”
The paper relies on this without support.
LFE and LFI are by far the most popular ILP learning settings.
“LFE and LFI are by far the most popular learning settings, so we only cover these two.”
The paper relies on this without support.
A definite logic program has only one model (the least Herbrand model), whereas an ASP program can have one, many, or even no models (answer sets).
“Whereas a definite logic program has only one model (the least Herbrand model), an ASP program can have one, many, or even no models (answer sets).”
The paper relies on this without support.
ASP supports additional language features, such as aggregates and weak and hard constraints.
“ASP also supports additional language features, such as aggregates and weak and hard constraints.”
The paper relies on this without support.
A key concept in ILP is the generality order over hypotheses (logic programs).
“A key concept in ILP is the generality order over hypotheses (logic programs).”
The paper relies on this without support.
A hypothesis can be a single clause or multiple clauses.
“A hypothesis can be a single clause or multiple clauses.”
The paper relies on this without support.
Often, a single clause is insufficient to describe a target concept.
“Often, a single clause is insufficient to describe a target concept.”
The paper relies on this without support.
The LFE problem in Definition 2 is general.
“The LFE problem in Definition 2 is general.”
The paper relies on this without support.
ILP systems impose strong restrictions on X, B, and H.
“ILP systems impose strong restrictions on X , B , and H .”
The paper relies on this without support.
Some ILP systems restrict X to only contain atoms whereas others allow clauses.
“For instance, some restrict X to only contain atoms whereas others allow clauses.”
The paper relies on this without support.
Some ILP systems restrict H to contain only Datalog clauses.
“Some restrict H to contain only Datalog clauses.”
The paper relies on this without support.
Training examples are often noisy.
“However, training examples are often noisy, so it is difficult to find a hypothesis that is both complete and consistent.”
The paper relies on this without support.
Reasoning about full clausal theories is computationally expensive.
“However, reasoning about full clausal theories is computationally expensive, so most systems learn fragments of clausal logic, usually definite programs.”
The paper relies on this without support.
Many practical applications require non-monotonic reasoning.
“One motivation for learning normal programs (Section 2.3.1) is that many practical applications require non-monotonic reasoning.”
The paper relies on this without support.
It is often simpler to express a concept with negation as failure (NAF).
“Moreover, it is often simpler to express a concept with negation as failure (NAF).”
The authors state this as an assumption.
When learning from interpretations, every example is completely specified: every atom in the interpretation has to be true or false, and there is no room for missing values.
“When learning from interpretations, it is implicitly assumed that every example is completely specified. That is, every atom in the interpretation has to be true or false, and there is no room for missing values.”
The paper relies on this without support.
ILP has traditionally relied on predefined and hand-crafted background knowledge, often designed by domain experts.
“ILP has traditionally relied on predefined and hand-crafted BK, often designed by domain experts.”
The paper relies on this without support.
Most ILP systems can only use background knowledge provided by a user.
“This situation is a major problem, as most systems can only use BK provided by a user.”
The paper relies on this without support.
ILP still heavily relies on much human input to solve a problem.
“However, ILP still heavily relies on much human input to solve a problem.”
The paper relies on this without support.
Addressing the problem of too much background knowledge has been under-researched.
“Addressing the problem of too much BK has been under-researched.”
The authors state this as an assumption.
The target hypothesis is in both hypothesis spaces.
“assuming that the target hypothesis is in both spaces.”
The paper relies on this without support.
There is little work determining which metarules to use for a given learning task.
“Despite their widespread use, there is little work determining which metarules to use for a given learning task.”
The paper relies on this without support.
These approaches assume suitable metarules as input or use metarules without any theoretical guarantees.
“Instead, these approaches assume suitable metarules as input or use metarules without any theoretical guarantees.”
The paper relies on this without support.
Aleph has good empirical performance.
“it has good empirical performance”
The paper relies on this without support.
Other ILP systems usually struggle to handle numerical data.
“Indeed, TILDE is an exception among ILP systems, which usually struggle to handle numerical data.”
The paper relies on this without support.
ASPAL's simplicity has inspired other approaches, notably ILASP.
“A major advantage of ASPAL is its sheer simplicity, which has inspired other approaches, notably ILASP.”
The paper relies on this without support.
Many natural language processing tasks require an understanding of the syntax and semantics of the language.
“Many natural language processing tasks require an understanding of the syntax and semantics of the language.”
The paper relies on this without support.
Metagol learns recursive programs.
“Metagol supports PI, learning recursive programs, and is guaranteed to learn the smallest program.”
The paper relies on this without support.
Metagol is guaranteed to learn the smallest program.
“Metagol supports PI, learning recursive programs, and is guaranteed to learn the smallest program.”
The paper relies on this without support.
Reaching human-level AI is a desirable goal.
“Russell (2019) argues that the automatic invention of new high-level concepts is the most important step needed to reach human-level AI.”
“To reach human-level AI, we would expect a learner to learn thousands or even millions of concepts.”
The paper relies on this without support.
Wider adoption of ILP both inside and outside academia is desirable.
“For ILP to be more widely adopted both inside and outside of academia, we must develop more standardised, user-friendly, and better-engineered tools.”
The paper relies on this without support.
Improving learning performance is a desirable goal.
“The central goal of representation learning coincides with the one behind PI: improving learning performance by changing the representation of a problem.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 1.3 Scenario 3: Program Synthesis · p. 4
“pivot(3,[4,1,5,2],[1,2],[4,5]).”
§ 1.3 Scenario 3: Program Synthesis · p. 4
“partition(Pivot,A,L,R)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 5.4 Recursion · p. 37
“last(A,B):tail(A,C),tail(C,D),tail(D,E),empty(E),head(E,B).”
§ 5.4 Recursion · p. 37
“without recursion, a system would need to learn a separate clause to find the last element for each list of length n”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 4.4.1 Mode Declarations · p. 25
“By contrast, the following rules are all mode consistent: ``` target(A,B):tail(A,C),head(C,B). target(A,B):tail(A,C),tail(C,D),equal(C,D),head(A,B). target(A,B):tail(A,C),member(C,B). ```”
§ 4.4.1 Mode Declarations · p. 25
“modeh(1,target(+list,-char)). modeb(*,head(+list,-char)). modeb(*,tail(+list,-list)). modeb(1,member(+list,-list)). modeb(1,equal(+char,-char)). modeb(*,empty(+list)).”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 3. Inductive Logic Programming · p. 15
“It does not, however, weakly subsume it as the number of literals is different.”
§ 2.4 Generality · p. 15
“Definition 1 (Clausal subsumption) . A clause C 1 subsumes a clause C 2 if and only if there exists a substitution θ such that C 1 θ ⊆ C 2 .”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 2.3.1 Non-Monotonic Logic · p. 14
“Whereas a definite logic program has only one model (the least Herbrand model), an ASP program can have one, many, or even no models (answer sets).”
§ 2.2 Semantics · p. 12
“A Herbrand interpretation I is a Herbrand model of a clause if for all substitutions θ for which the body literals, after applying the substitution θ , are true in I , at least one of the head literals is also true in I .”
Citations
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“For this reason, ILP naturally supports lifelong (Silver et al., 2013), multi-task (Caruana, 1997), and transfer learning (Torrey & Shavlik, 2009), which are considered essential for human-like AI (Lake et al., 2016).”
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Cited by
Sorted by citations
Learning programs by learning from failures
Cropper, A., & Morel, R. (2021) · Machine Learning · doi:10.1007/s10994-020-05934-z · Cited by 86
“We focus on inductive logic programming (ILP) (Muggleton 1991; Cropper and Dumancic 2020).”
BackgroundMethodSelf-citationGeneralized Planning in PDDL Domains with Pretrained Large Language Models
Silver, T., Dan, S., Srinivas, K., Tenenbaum, J. B., Kaelbling, L. P., & Katz, M. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i18.30006 · Cited by 150
Inductive logic programming at 30
Cropper, A., Dumančić, S., Evans, R., & Muggleton, S. H. (2022) · Machine Learning · doi:10.1007/s10994-021-06089-1 · Cited by 61
“1 We do not introduce ILP in detail and refer the reader to the introductory paper of Cropper and Dumancic [17] or the textbooks of Nienhuys-Cheng and Wolf [89] and De Raedt [29].”
BackgroundSelf-citationLearning Symbolic Operators for Task and Motion Planning
Silver, T., Chitnis, R., Tenenbaum, J. B., et al. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9635941 · Cited by 42
“In terms of taxonomy, our proposed algorithm can be seen as a bottom-up inductive logic programming (ILP) algorithm, although it falls outside of the typical problem setting considered in ILP [26], [27].”
Methodbabble: Learning Better Abstractions with E-Graphs and Anti-unification
Cao, D., Kunkel, R., Nandi, C., Willsey, M., Tatlock, Z., & Polikarpova, N. (2023) · Proceedings of the ACM on Programming Languages · doi:10.1145/3571207 · Cited by 38
“It is the core idea behind bottom-up Inductive Logic Programming [Cropper and Dumancic 2022], and has also been used for software clone detection [Bulychev et al. 2010], programming by example [Raza et al. 2014], and learning repetitive code edits [Meng et al. 2013; Rolim et al. 2017].”
Method
Metadata
- Authors
- Cropper, A., & Dumančić, S.
- Affiliations
- University of Oxford (GB)
- Delft University of Technology (NL)
- Venue
- Journal of Artificial Intelligence Research
- Publisher
- AI Access Foundation
- Published
- 2022-06-15
- Volume
- 74
- Pages
- 765-850
- ISSN
- 1076-9757 (ISSN-L)
- OpenAlex
- W3065734471
- Semantic Scholar
- 97032dfb13adbb404f731592dbeaa5f21acc102b
- Cited by
- 83
- References
- 286
- Citations by year
- 2026: 12 · 2025: 31 · 2024: 12 · 2023: 16 · 2022: 5
- FWCI
- 5.14
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Journal of Artificial Intelligence Research (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- Engineering and Physical Sciences Research Council (EP/V040340/1)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Keywords
- inductive logic programming, ALEPH, tilde
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-19, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-19 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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