The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages

Jan Hajič*, Massimiliano Ciaramita, Richard Johansson, Daisuke Kawahara, Maria Antònia Màrti, Lluís Marquez, Adam Meyers, Joakim Nivre, Sebastian Padó, Jan Štěpańek, Pavel Straňak, Mihai Surdeanu, Nianwen Xue, Yi Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 13th Conference on Computational Natural Language Learning
Subtitle of host publicationShared Task, CoNLL 2009
EditorsJan Hajic
PublisherAssociation for Computational Linguistics (ACL)
Pages1-18
Number of pages18
ISBN (Electronic)9781932432299
Publication statusPublished - 2009
Externally publishedYes
Event13th Conference on Computational Natural Language Learning, CoNLL 2009 - Boulder, CO, United States
Duration: 2009 Jun 42009 Jun 4

Publication series

NameProceedings of the 13th Conference on Computational Natural Language Learning: Shared Task, CoNLL 2009

Conference

Conference13th Conference on Computational Natural Language Learning, CoNLL 2009
Country/TerritoryUnited States
CityBoulder, CO
Period09/6/409/6/4

ASJC Scopus subject areas

  • Linguistics and Language
  • Human-Computer Interaction
  • Artificial Intelligence

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