Abstract
Semantic information about entities, specifically, how close in meaning two mentions are to each other, can become very useful for the task of co-reference resolution. One of the most well-researched and widely used forms of presenting this information are measures of semantic similarity and semantic relatedness. These metrics are often computed, relying upon the structure of a thesaurus, but it is also possible to use alternative resources. One such source is Wikipedia, which possesses the category structure similar to that of a thesaurus. In this work we describe an attempt to use semantic relatedness measures, calculated on thesaurus and Wikipedia data, to improve the quality of a co-reference resolution system for Russian language. The results show that this is a viable solution and that combining the two sources yields the most gain in quality.- Anthology ID:
- 2019.gwc-1.6
- Volume:
- Proceedings of the 10th Global Wordnet Conference
- Month:
- July
- Year:
- 2019
- Address:
- Wroclaw, Poland
- Editors:
- Piek Vossen, Christiane Fellbaum
- Venue:
- GWC
- SIG:
- SIGLEX
- Publisher:
- Global Wordnet Association
- Note:
- Pages:
- 39–45
- Language:
- URL:
- https://aclanthology.org/2019.gwc-1.6
- DOI:
- Cite (ACL):
- Ilya Azerkovich. 2019. Using Thesaurus Data to Improve Coreference Resolution for Russian. In Proceedings of the 10th Global Wordnet Conference, pages 39–45, Wroclaw, Poland. Global Wordnet Association.
- Cite (Informal):
- Using Thesaurus Data to Improve Coreference Resolution for Russian (Azerkovich, GWC 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2019.gwc-1.6.pdf