Abstract
The paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model was trained on examples from Slovene Wikipedia which was then used to find well-formed definitions among the extracted candidates. The results of the experiment are encouraging, with accuracy ranging from 67% to 71%. The paper also addresses some drawbacks of the approach and suggests ways to overcome them in future work.- Anthology ID:
- L10-1089
- Volume:
- Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
- Month:
- May
- Year:
- 2010
- Address:
- Valletta, Malta
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf
- DOI:
- Cite (ACL):
- Darja Fišer, Senja Pollak, and Špela Vintar. 2010. Learning to Mine Definitions from Slovene Structured and Unstructured Knowledge-Rich Resources. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
- Cite (Informal):
- Learning to Mine Definitions from Slovene Structured and Unstructured Knowledge-Rich Resources (Fišer et al., LREC 2010)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf