A machine learning approach to pronoun resolution in spoken dialogue
- We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NP- and non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron’s (2002) manually tuned system.
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| Author: | Michael StrubeGND, Mark-Christoph MüllerORCiDGND |
|---|---|
| URN: | urn:nbn:de:bsz:mh39-111560 |
| URL: | https://aclanthology.org/P03-1022 |
| DOI: | https://doi.org/10.3115/1075096.1075118 |
| Parent Title (English): | Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics. July 7 - 12, 2003, Sapporo, Japan |
| Publisher: | Association for Computational Linguistics |
| Place of publication: | Stroudsburg, Pennsylvania |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of first Publication: | 2003 |
| Date of Publication (online): | 2022/07/26 |
| Publishing Institution: | Leibniz-Institut für Deutsche Sprache (IDS) |
| Publicationstate: | Veröffentlichungsversion |
| Reviewstate: | Peer-Review |
| GND Keyword: | Dialog; Entscheidungsbaum; Gesprochene Sprache; Korpus <Linguistik>; Maschinelles Lernen; Nominalphrase; Pronomen |
| First Page: | 168 |
| Last Page: | 175 |
| DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
| Open Access?: | ja |
| Linguistics-Classification: | Computerlinguistik |
| Licence (English): |  Creative Commons - Attribution-NonCommercial-ShareAlike 3.0 Unported |