Learning to Mine Definitions from Slovene Structured and Unstructured Knowledge-Rich Resources

Darja Fišer, Senja Pollak, Špela Vintar


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
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Mike Rosner, Daniel Tapias
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:
Bibkey:
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)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/141_Paper.pdf