Vlachos, A. and Clark, S. (2014) A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing. Transactions of the Association for Computational Linguistics, 2. 547 - 559 . ISSN 2307-387X
Abstract
Semantic parsing is the task of translating natural language utterances into a machine- interpretable meaning representation. Most approaches to this task have been evaluated on a small number of existing corpora which assume that all utterances must be interpreted according to a database and typically ignore context. In this paper we present a new, pub- licly available corpus for context-dependent semantic parsing. The MRL used for the an- notation was designed to support a portable, interactive tourist information system. We develop a semantic parser for this corpus by adapting the imitation learning algorithm DAGGER without requiring alignment infor- mation during training. DAGGER improves upon independently trained classifiers by 9.0 and 4.8 points in F-score on the development and test sets respectively.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Association for Computational Linguistics. This work is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Nov 2015 18:01 |
Last Modified: | 19 Nov 2015 18:01 |
Published Version: | https://tacl2013.cs.columbia.edu/ojs/index.php/tac... |
Status: | Published |
Publisher: | Association for Computational Linguistic |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:91377 |