The DOI matches its OpenAlex record; 4 of the 4 references it cites were found in a registry or an index.
Dependency Parsing
Open accessOverview
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
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Recognition and parsing of context-free languages in time n3
Younger, D. H. (1967) · Information and Control · doi:10.1016/s0019-9958(67)80007-x · Cited by 935
Edmonds, J. (1967) · Journal of Research of the National Bureau of Standards Section B Mathematics and Mathematical Physics · doi:10.6028/jres.071b.032 · Cited by 731
Multilingual dependency analysis with a two-stage discriminative parser
McDonald, R., Lerman, K., & Pereira, F. (2006) · Proceedings of the Tenth Conference on Computational Natural Language Learning - CoNLL-X '06 · doi:10.3115/1596276.1596317 · Cited by 223
Self-citation
Cited by
Neural Network Methods for Natural Language Processing
Goldberg, Y. (2017) · Synthesis Lectures on Human Language Technologies · doi:10.1007/978-3-031-02165-7 · Cited by 821
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
Lee, H., Chang, A., Peirsman, Y., Chambers, N., Surdeanu, M., & Jurafsky, D. (2013) · Computational Linguistics · doi:10.1162/coli_a_00152 · Cited by 384
Tesnière, L. (2015) · John Benjamins Publishing Company eBooks · doi:10.1075/z.185 · Cited by 383
Tool Learning with Foundation Models
Qin, Y., Hu, S., Lin, Y., Chen, W., Ding, N., Cui, G., Zeng, Z., Huang, Y., Xiao, C., Han, C., et al. (2023) · arXiv · doi:10.48550/arxiv.2304.08354 · Cited by 184
(2024) · doi:10.1145/3704435 · Cited by 184
Metadata
- Authors
- Kübler, S., McDonald, R., & Nivre, J.
- Venue
- Synthesis lectures on human language technologies
- Publisher
- Morgan & Claypool Publishers
- Published
- 2009-01-01
- Volume
- 2
- Issue
- 1
- Pages
- 1-127
- ISSN
- 1947-4040 (ISSN-L)
- OpenAlex
- W4210956481
- Cited by
- 172
- References
- 4
- FWCI
- 3.98
- 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: Dependency Parsing. https://app.cochat.ai/papers/10.2200/s00169ed1v01y200901hlt002
- The paper
- Kübler, S., McDonald, R., & Nivre, J. (2009). Dependency Parsing. Synthesis lectures on human language technologies. https://doi.org/10.2200/s00169ed1v01y200901hlt002
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.