Abstract
This paper evaluates the impact of external lexical resources into a CRF-based joint Multiword Segmenter and Part-of-Speech Tagger. We especially show different ways of integrating lexicon-based features in the tagging model. We display an absolute gain of 0.5% in terms of f-measure. Moreover, we show that the integration of lexicon-based features significantly compensates the use of a small training corpus.- Anthology ID:
- L12-1350
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 646–650
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/610_Paper.pdf
- DOI:
- Cite (ACL):
- Matthieu Constant and Isabelle Tellier. 2012. Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 646–650, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger (Constant & Tellier, LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/610_Paper.pdf