Abstract
Although represented as such in wordnets, word senses are not discrete. To handle word senses as fuzzy objects, we exploit the graph structure of synonymy pairs acquired from different sources to discover synsets where words have different membership degrees that reflect confidence. Following this approach, a wide-coverage fuzzy thesaurus was discovered from a synonymy network compiled from seven Portuguese lexical-semantic resources. Based on a crowdsourcing evaluation, we can say that the quality of the obtained synsets is far from perfect but, as expected in a confidence measure, it increases significantly for higher cut-points on the membership and, at a certain point, reaches 100% correction rate.- Anthology ID:
- L16-1687
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 4333–4340
- Language:
- URL:
- https://aclanthology.org/L16-1687
- DOI:
- Cite (ACL):
- Hugo Gonçalo Oliveira and Fábio Santos. 2016. Discovering Fuzzy Synsets from the Redundancy in Different Lexical-Semantic Resources. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4333–4340, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Discovering Fuzzy Synsets from the Redundancy in Different Lexical-Semantic Resources (Oliveira & Santos, LREC 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/L16-1687.pdf