The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Transition network grammars for natural language analysis
Open accessAbstract
The use of augmented transition network grammars for the analysis of natural language sentences is described. Structure-building actions associated with the arcs of the grammar network allow for the reordering, restructuring, and copying of constituents necessary to produce deep-structure representations of the type normally obtained from a transformational analysis, and conditions on the arcs allow for a powerful selectivity which can rule out meaningless analyses and take advantage of semantic information to guide the parsing. The advantages of this model for natural language analysis are discussed in detail and illustrated by examples. An implementation of an experimental parsing system for transition network grammars is briefly described.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
ASPECTS OF THE THEORY OF SYNTAX
Chomsky, N. (1964) · doi:10.21236/ad0616323 · Cited by 13,587
Cited by
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
Erman, L. D., Hayes-Roth, F., Lesser, V. R., & Reddy, D. R. (1980) · ACM Computing Surveys · doi:10.1145/356810.356816 · Cited by 1,357
Establishing and maintaining long-term human-computer relationships
Bickmore, T. W., & Picard, R. W. (2005) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1067860.1067867 · Cited by 1,333
Artificial Intelligence: A New Synthesis
(1998) · Elsevier eBooks · doi:10.1016/c2009-0-27773-7 · Cited by 1,163
(1997) · Cited by 914
Establishing the computer-patient working alliance in automated health behavior change interventions
Bickmore, T., Gruber, A., & Picard, R. (2005) · Patient Education and Counseling · doi:10.1016/j.pec.2004.09.008 · Cited by 494
Metadata
- Authors
- Woods, W. A.
- Venue
- Communications of the ACM
- Published
- 1970-10
- Volume
- 13
- Issue
- 10
- Pages
- 591-606
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2035032881
- Cited by
- 1,323
- References
- 1
- FWCI
- 27.76
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Transition network grammars for natural language analysis. https://app.cochat.ai/papers/10.1145/355598.362773
- The paper
- Woods, W. A. (1970). Transition network grammars for natural language analysis. Communications of the ACM. https://doi.org/10.1145/355598.362773
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.