Abstract
This paper empirically evaluates the performances of different state-of-the-art distributional models in a nominal lexical semantic classification task. We consider models that exploit various types of distributional features, which thereby provide different representations of nominal behavior in context. The experiments presented in this work demonstrate the advantages and disadvantages of each model considered. This analysis also considers a combined strategy that we found to be capable of leveraging the bottlenecks of each model, especially when large robust data is not available.- Anthology ID:
- L14-1471
- 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:
- 4366–4373
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/583_Paper.pdf
- DOI:
- Cite (ACL):
- Lauren Romeo, Gianluca Lebani, Núria Bel, and Alessandro Lenci. 2014. Choosing which to use? A study of distributional models for nominal lexical semantic classification. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4366–4373, Reykjavik, Iceland. European Language Resources Association (ELRA).
- Cite (Informal):
- Choosing which to use? A study of distributional models for nominal lexical semantic classification (Romeo et al., LREC 2014)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/583_Paper.pdf