The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Immediate-head parsing for language models
Open accessAbstract
We present two language models based upon an "immediate-head" parser --- our name for a parser that conditions all events below a constituent c upon the head of c. While all of the most accurate statistical parsers are of the immediate-head variety, no previous grammatical language model uses this technology. The perplexity for both of these models significantly improve upon the trigram model base-line as well as the best previous grammar-based language model. For the better of our two models these improvements are 24% and 14% respectively. We also suggest that improvement of the underlying parser should significantly improve the model's perplexity and that even in the near term there is a lot of potential for improvement in immediate-head language models.
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
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
Head-Driven Statistical Models for Natural Language Parsing
Collins, M. (2003) · Computational Linguistics · doi:10.1162/089120103322753356 · Cited by 1,826
(1999) · Cited by 1,521
Proceedings of the 24th annual meeting on Association for Computational Linguistics -
(1986) · doi:10.3115/981131 · Cited by 1,081
Three generative, lexicalised models for statistical parsing
Collins, M. (1997) · Proceedings of the 35th annual meeting on Association for Computational Linguistics - · doi:10.3115/976909.979620 · Cited by 743
Discriminative Reranking for Natural Language Parsing
Collins, M., & Koo, T. (2005) · Computational Linguistics · doi:10.1162/0891201053630273 · Cited by 710
Statistical decision-tree models for parsing
Magerman, D. M. (1995) · Proceedings of the 33rd annual meeting on Association for Computational Linguistics - · doi:10.3115/981658.981695 · Cited by 567
An Efficient Probabilistic Context-Free Parsing Algorithm that Computes Prefix Probabilities
Stolcke, A. (1994) · arXiv (Cornell University) · doi:10.48550/arxiv.cmp-lg/9411029 · Cited by 336
Probabilistic Top-Down Parsing and Language Modeling
Roark, B. (2001) · Computational Linguistics · doi:10.1162/089120101750300526 · Cited by 329
Eugene Charniak, D. (1996) · National Conference on Artificial Intelligence · Cited by 266
Cited by
Accurate unlexicalized parsing
Klein, D., & Manning, C. D. (2003) · Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - ACL '03 · doi:10.3115/1075096.1075150 · Cited by 3,008
Multiword Expressions: A Pain in the Neck for NLP
Sag, I. A., Baldwin, T., Bond, F., Copestake, A., & Flickinger, D. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-45715-1_1 · Cited by 1,016
Composition in Distributional Models of Semantics
Mitchell, J., & Lapata, M. (2010) · Cognitive Science · doi:10.1111/j.1551-6709.2010.01106.x · Cited by 960
A bit of progress in language modeling
Goodman, J. T. (2001) · Computer Speech & Language · doi:10.1006/csla.2001.0174 · Cited by 469
The Importance of Syntactic Parsing and Inference in Semantic Role Labeling
Punyakanok, V., Roth, D., & Yih, W.-T. (2008) · Computational Linguistics · doi:10.1162/coli.2008.34.2.257 · Cited by 391
Metadata
- Authors
- Charniak, E.
- Venue
- Proceedings of the 39th Annual Meeting on Association for Computational Linguistics - ACL '01
- Published
- 2001
- Pages
- 124-131
- OpenAlex
- W2155693943
- Cited by
- 293
- References
- 15
- FWCI
- 15.86
- Type
- conference paper
- 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: Immediate-head parsing for language models. https://app.cochat.ai/papers/10.3115/1073012.1073029
- The paper
- Charniak, E. (2001). Immediate-head parsing for language models. Proceedings of the 39th Annual Meeting on Association for Computational Linguistics - ACL '01. https://doi.org/10.3115/1073012.1073029
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.