@article{vlachos-clark-2014-new,
title = "A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing",
author = "Vlachos, Andreas and
Clark, Stephen",
editor = "Lin, Dekang and
Collins, Michael and
Lee, Lillian",
journal = "Transactions of the Association for Computational Linguistics",
volume = "2",
year = "2014",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/Q14-1042",
doi = "10.1162/tacl_a_00202",
pages = "547--560",
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, publicly available corpus for context-dependent semantic parsing. The MRL used for the annotation 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 information 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.",
}
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%0 Journal Article
%T A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing
%A Vlachos, Andreas
%A Clark, Stephen
%J Transactions of the Association for Computational Linguistics
%D 2014
%V 2
%I MIT Press
%C Cambridge, MA
%F vlachos-clark-2014-new
%X 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, publicly available corpus for context-dependent semantic parsing. The MRL used for the annotation 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 information 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.
%R 10.1162/tacl_a_00202
%U https://aclanthology.org/Q14-1042
%U https://doi.org/10.1162/tacl_a_00202
%P 547-560
Markdown (Informal)
[A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing](https://aclanthology.org/Q14-1042) (Vlachos & Clark, TACL 2014)
ACL