The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages
Open accessAbstract
For the 11th straight year, the Conference on Computational Natural Language Learning has been accompanied by a shared task whose purpose is to promote natural language processing applications and evaluate them in a standard setting. In 2009, the shared task was dedicated to the joint parsing of syntactic and semantic dependencies in multiple languages. This shared task combines the shared tasks of the previous five years under a unique dependency-based formalism similar to the 2008 task. In this paper, we define the shared task, describe how the data sets were created and show their quantitative properties, report the results and summarize the approaches of the participating systems.
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
WordNet: An Electronic Lexical Database
Kilgarriff, A., & Fellbaum, C. (2000) · Language · doi:10.2307/417141 · Cited by 11,464
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
The Proposition Bank: An Annotated Corpus of Semantic Roles
Palmer, M., Gildea, D., & Kingsbury, P. (2005) · Computational Linguistics · doi:10.1162/0891201053630264 · Cited by 2,273
Non-projective dependency parsing using spanning tree algorithms
McDonald, R., Pereira, F., Ribarov, K., & Hajič, J. (2005) · Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05 · doi:10.3115/1220575.1220641 · Cited by 847
Self-citationThe Penn Chinese TreeBank: Phrase structure annotation of a large corpus
XUE, N., XIA, F., CHIOU, F.-D., & PALMER, M. (2005) · Natural Language Engineering · doi:10.1017/s135132490400364x · Cited by 666
Self-citationThe CoNLL 2007 Shared Task on Dependency Parsing
Nivre, J., Hall, J., Kübler, S., McDonald, R., Nilsson, J., Riedel, S., & Yüret, D. (2007) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · Cited by 663
Self-citationThe CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies
Surdeanu, M., Johansson, R., Meyers, A., Màrquez, L., & Nivre, J. (2008) · Proceedings of the Twelfth Conference on Computational Natural Language Learning - CoNLL '08 · doi:10.3115/1596324.1596352 · Cited by 491
Self-citationThe NomBank Project: An Interim Report
Meyers, A., Reeves, R., MacLeod, C. A., Szekely, R., Zielinska, V., Young, B., & Grishman, R. (2004) · Cited by 318
Self-citationAnCora: Multilevel Annotated Corpora for Catalan and Spanish
Taulé, M., Martí, M. A., & Recasens, M. V. (2008) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/3e9335sw8bvc · Cited by 296
Self-citationExperiments with a Higher-Order Projective Dependency Parser
Carreras, X. (2007) · Cited by 233
Cited by
A Survey of the Usages of Deep Learning for Natural Language Processing
Otter, D. W., Medina, J. R., & Kalita, J. K. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2979670 · Cited by 1,836
(2012) · Cited by 618
Biases in Large Language Models: Origins, Inventory, and Discussion
Navigli, R., Conia, S., & Ross, B. (2023) · Journal of Data and Information Quality · doi:10.1145/3597307 · Cited by 364
Eyigoz, E., Courson, M., Sedeño, L., Rogg, K., Orozco-Arroyave, J. R., Nöth, E., Skodda, S., Trujillo, N., Rodríguez, M., Rusz, J., et al. (2020) · Cortex · doi:10.1016/j.cortex.2020.08.020 · Cited by 44
Metadata
- Authors
- Hajič, J., Štěpánek, J., Straňák, P., Surdeanu, M., Xue, N., Zhang, Y., Ciaramita, M., Johansson, R., Kawahara, D., Martí, M. A., Màrquez, L., Meyers, A., Nivre, J., & Padó, S.
- Venue
- Proceedings of the Thirteenth Conference on Computational Natural Language Learning Shared Task - CoNLL '09
- Published
- 2009
- Pages
- 1
- OpenAlex
- W2142222368
- Cited by
- 339
- References
- 16
- FWCI
- 26.32
- Type
- conference paper
- Language
- en
- Open access
- gold
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: The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages. https://app.cochat.ai/papers/10.3115/1596409.1596411
- The paper
- Hajič, J., Štěpánek, J., Straňák, P., Surdeanu, M., Xue, N., Zhang, Y., Ciaramita, M., Johansson, R., Kawahara, D., Martí, M. A., Màrquez, L., Meyers, A., Nivre, J., & Padó, S. (2009). The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages. Proceedings of the Thirteenth Conference on Computational Natural Language Learning Shared Task - CoNLL '09. https://doi.org/10.3115/1596409.1596411
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.