Abstract
We introduce a new CCG parsing model
which is factored on lexical category assignments. Parsing is then simply a deterministic search for the most probable
category sequence that supports a CCG
derivation. The parser is extremely simple,
with a tiny feature set, no POS tagger, and
no statistical model of the derivation or
dependencies. Formulating the model in
this way allows a highly effective heuristic for A* parsing, which makes parsing
extremely fast. Compared to the standard
C&C CCG parser, our model is more accurate out-of-domain, is four times faster,
has higher coverage, and is greatly simplified. We also show that using our parser
improves the performance of a state-of-the-art question answering system.
Original language | English |
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Title of host publication | Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) |
Place of Publication | Doha, Qatar |
Publisher | Association for Computational Linguistics |
Pages | 990-1000 |
Number of pages | 11 |
DOIs | |
Publication status | Published - 1 Oct 2014 |
Event | 2014 Conference on Empirical Methods in Natural Language Processing - Doha, Qatar Duration: 25 Oct 2014 → 29 Oct 2014 http://emnlp2014.org/ |
Conference
Conference | 2014 Conference on Empirical Methods in Natural Language Processing |
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Abbreviated title | EMNLP 2014 |
Country/Territory | Qatar |
City | Doha |
Period | 25/10/14 → 29/10/14 |
Internet address |
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Mark Steedman
- School of Informatics - Professor
- Institute of Language, Cognition and Computation
- Language, Interaction, and Robotics
Person: Academic: Research Active