Abstract
Sluice resolution in English is the problemof finding antecedents of wh-fronted ellipses.Previous work has relied on handcraftedfeatures over syntax trees that scalepoorly to other languages and domains;in particular, to dialogue, which is one ofthe most interesting applications of sluiceresolution. Syntactic information is arguablyimportant for sluice resolution, butwe show that multi-task learning with partialparsing as auxiliary tasks effectivelycloses the gap and buys us an additional9% error reduction over previous work.Since we are not directly relying on featuresfrom partial parsers, our system ismore robust to domain shifts, giving a26% error reduction on embedded sluicesin dialogue.
Original language | English |
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Title of host publication | Proceedings, 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies : (Long Papers) |
Volume | 1 |
Publisher | Association for Computational Linguistics |
Publication date | 2018 |
Pages | 236–241 |
Publication status | Published - 2018 |
Event | 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - New Orleans, United States Duration: 1 Jun 2018 → 6 Jun 2018 |
Conference
Conference | 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies |
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Country/Territory | United States |
City | New Orleans |
Period | 01/06/2018 → 06/06/2018 |