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.
CitationCarreras, X.; Surdeanu, M.; Màrquez, L. Projective dependency parsing with perceptron. A: Conference on Computational Natural Language Learning. "Tenth Conference on Computational Natural Language Learning (CoNLL-X)". New York City: 2010, p. 181-185.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: firstname.lastname@example.org