Konferenzbeitrag
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.
- Sprache
-
Englisch
- Thema
-
Maschinelles Lernen
Pronomen
Dialog
Gesprochene Sprache
Entscheidungsbaum
Korpus <Linguistik>
Nominalphrase
Sprache
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Strube, Michael
Müller, Mark-Christoph
- Ereignis
-
Veröffentlichung
- (wer)
-
Stroudsburg, Pennsylvania : Association for Computational Linguistics
Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)
- (wann)
-
2022-07-26
- URN
-
urn:nbn:de:bsz:mh39-111560
- Letzte Aktualisierung
-
06.03.2025, 09:00 MEZ
Datenpartner
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Objekttyp
- Konferenzbeitrag
Beteiligte
- Strube, Michael
- Müller, Mark-Christoph
- Stroudsburg, Pennsylvania : Association for Computational Linguistics
- Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)
Entstanden
- 2022-07-26
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