Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features
Abstract
We present a supervised method for verb sense disambiguation based on VerbNet. Most previous supervised approaches to verb sense disambiguation create a classifier for each verb that reaches a frequency threshold. These methods, however, have a significant practical problem that they cannot be applied to rare or unseen verbs. In order to overcome this problem, we create a single classifier to be applied to rare or unseen verbs in a new text. This single classifier also exploits generalized semantic features of a verb and its modifiers in order to better deal with rare or unseen verbs. Our experimental results show that the proposed method achieves equivalent performance to per-verb classifiers, which cannot be applied to unseen verbs. Our classifier could be utilized to improve the classifications in lexical resources of verbs, such as VerbNet, in a semi-automatic manner and to possibly extend the coverage of these resources to new verbs.- Anthology ID:
- L14-1689
- Volume:
- Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
- Month:
- May
- Year:
- 2014
- Address:
- Reykjavik, Iceland
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 4210–4213
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/90_Paper.pdf
- DOI:
- Cite (ACL):
- Daisuke Kawahara and Martha Palmer. 2014. Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4210–4213, Reykjavik, Iceland. European Language Resources Association (ELRA).
- Cite (Informal):
- Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features (Kawahara & Palmer, LREC 2014)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/90_Paper.pdf