Projective dependency parsing with perceptron

Xavier Carreras, Mihai Surdeanu, Lluìs Màrquez

Research output: Contribution to conferencePaperpeer-review

13 Scopus citations


We describe an online learning dependency parser for the CoNLL-X Shared Task, based on the bottom-up projective algorithm of Eisner (2000). We experiment with a large feature set that models: the tokens involved in dependencies and their immediate context, the surfacetext distance between tokens, and the syntactic context dominated by each dependency. In experiments, the treatment of multilingual information was totally blind.

Original languageEnglish (US)
StatePublished - 2006
Event10th Conference on Computational Natural Language Learning, CoNLL-X - New York, NY, United States
Duration: Jun 8 2006Jun 9 2006


Conference10th Conference on Computational Natural Language Learning, CoNLL-X
Country/TerritoryUnited States
CityNew York, NY

ASJC Scopus subject areas

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


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