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        <title>Semantic Parsing for Task Oriented Dialog using Hierarchical Representations</title>
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        <namePart type="given">Sonal</namePart>
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        <namePart type="given">Rushin</namePart>
        <namePart type="family">Shah</namePart>
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    <name type="personal">
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    <name type="personal">
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    <name type="personal">
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            <title>Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</title>
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    <abstract>Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token, and thus cannot model complex compositional requests. Alternative semantic parsing systems have represented queries as logical forms, but these are challenging to annotate and parse. We propose a hierarchical annotation scheme for semantic parsing that allows the representation of compositional queries, and can be efficiently and accurately parsed by standard constituency parsing models. We release a dataset of 44k annotated queries (http://fb.me/semanticparsingdialog), and show that parsing models outperform sequence-to-sequence approaches on this dataset.</abstract>
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%0 Conference Proceedings
%T Semantic Parsing for Task Oriented Dialog using Hierarchical Representations
%A Gupta, Sonal
%A Shah, Rushin
%A Mohit, Mrinal
%A Kumar, Anuj
%A Lewis, Mike
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F gupta-etal-2018-semantic-parsing
%X Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token, and thus cannot model complex compositional requests. Alternative semantic parsing systems have represented queries as logical forms, but these are challenging to annotate and parse. We propose a hierarchical annotation scheme for semantic parsing that allows the representation of compositional queries, and can be efficiently and accurately parsed by standard constituency parsing models. We release a dataset of 44k annotated queries (http://fb.me/semanticparsingdialog), and show that parsing models outperform sequence-to-sequence approaches on this dataset.
%R 10.18653/v1/D18-1300
%U https://aclanthology.org/D18-1300
%U https://doi.org/10.18653/v1/D18-1300
%P 2787-2792

Markdown (Informal)

[Semantic Parsing for Task Oriented Dialog using Hierarchical Representations](https://aclanthology.org/D18-1300) (Gupta et al., EMNLP 2018)

• Semantic Parsing for Task Oriented Dialog using Hierarchical Representations (Gupta et al., EMNLP 2018)

ACL

• Sonal Gupta, Rushin Shah, Mrinal Mohit, Anuj Kumar, and Mike Lewis. 2018. Semantic Parsing for Task Oriented Dialog using Hierarchical Representations. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2787–2792, Brussels, Belgium. Association for Computational Linguistics.