Language Resources and Evaluation

, Volume 43, Issue 1, pp 71–85 | Cite as

Multilingual collocation extraction with a syntactic parser

Article

Abstract

An impressive amount of work was devoted over the past few decades to collocation extraction. The state of the art shows that there is a sustained interest in the morphosyntactic preprocessing of texts in order to better identify candidate expressions; however, the treatment performed is, in most cases, limited (lemmatization, POS-tagging, or shallow parsing). This article presents a collocation extraction system based on the full parsing of source corpora, which supports four languages: English, French, Spanish, and Italian. The performance of the system is compared against that of the standard mobile-window method. The evaluation experiment investigates several levels of the significance lists, uses a fine-grained annotation schema, and covers all the languages supported. Consistent results were obtained for these languages: parsing, even if imperfect, leads to a significant improvement in the quality of results, in terms of collocational precision (between 16.4 and 29.7%, depending on the language; 20.1% overall), MWE precision (between 19.9 and 35.8%; 26.1% overall), and grammatical precision (between 47.3 and 67.4%; 55.6% overall). This positive result bears a high importance, especially in the perspective of the subsequent integration of extraction results in other NLP applications.

Keywords

Collocation extraction Evaluation Hybrid methods Multilingual issues Syntactic parsing 

Notes

Acknowledgements

This work was supported in part by Swiss National Science Foundation grant no. 101412-103999. We wish to thank Jorge Antonio Leoni de León, Yves Scherrer and Vincenzo Pallotta for participating in the annotation task, as well as Stephanie Durrleman-Tame for proofreading the article. We are very grateful to the anonymous reviewers, whose comments and suggestions helped us to improve this paper.

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Language Technology Laboratory (LATL)University of GenevaGenevaSwitzerland

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