Disambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing

Ismail El Maarouf, Jane Bradbury, Vít Baisa, Patrick Hanks


Abstract
This paper reports the results of Natural Language Processing (NLP) experiments in semantic parsing, based on a new semantic resource, the Pattern Dictionary of English Verbs (PDEV) (Hanks, 2013). This work is set in the DVC (Disambiguating Verbs by Collocation) project , a project in Corpus Lexicography aimed at expanding PDEV to a large scale. This project springs from a long-term collaboration of lexicographers with computer scientists which has given rise to the design and maintenance of specific, adapted, and user-friendly editing and exploration tools. Particular attention is drawn on the use of NLP deep semantic methods to help in data processing. Possible contributions of NLP include pattern disambiguation, the focus of this article. The present article explains how PDEV differs from other lexical resources and describes its structure in detail. It also presents new classification experiments on a subset of 25 verbs. The SVM model obtained a micro-average F1 score of 0.81.
Anthology ID:
L14-1300
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1001–1006
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/34_Paper.pdf
DOI:
Bibkey:
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/34_Paper.pdf