Applying co-training to reference resolution
- In this paper, we investigate the practical applicability of Co-Training for the task of building a classifier for reference resolution. We are concerned with the question if Co-Training can significantly reduce the amount of manual labeling work and still produce a classifier with an acceptable performance.
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| Author: | Mark-Christoph MüllerORCiDGND, Stefan Rapp, Michael StrubeGND |
|---|---|
| URN: | urn:nbn:de:bsz:mh39-111649 |
| URL: | https://aclanthology.org/P02-1045/ |
| DOI: | https://doi.org/10.3115/1073083.1073142 |
| ISBN: | 1-55860-883-4 |
| Parent Title (English): | Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. 7 - 12 July 2002, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| Publisher: | Association for Computational Linguistics |
| Place of publication: | Stroudsburg, Pennsylvania |
| Editor: | Pierre Isabelle, Eugene Charniak, Dekang Lin |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of first Publication: | 2002 |
| Date of Publication (online): | 2022/07/28 |
| Publishing Institution: | Leibniz-Institut für Deutsche Sprache (IDS) |
| Publicationstate: | Veröffentlichungsversion |
| Reviewstate: | Peer-Review |
| Tag: | co-training; reference resolution |
| GND Keyword: | Computerlinguistik; Korpus <Linguistik> |
| First Page: | 352 |
| Last Page: | 359 |
| DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
| Open Access?: | ja |
| Linguistics-Classification: | Computerlinguistik |
| Licence (English): |  Creative Commons - Attribution-NonCommercial-ShareAlike 3.0 Unported |