@inproceedings{zou-lu-2018-learning,
    title = "Learning Cross-lingual Distributed Logical Representations for Semantic Parsing",
    author = "Zou, Yanyan  and
      Lu, Wei",
    editor = "Gurevych, Iryna  and
      Miyao, Yusuke",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P18-2107/",
    doi = "10.18653/v1/P18-2107",
    pages = "673--679",
    abstract = "With the development of several multilingual datasets used for semantic parsing, recent research efforts have looked into the problem of learning semantic parsers in a multilingual setup. However, how to improve the performance of a monolingual semantic parser for a specific language by leveraging data annotated in different languages remains a research question that is under-explored. In this work, we present a study to show how learning distributed representations of the logical forms from data annotated in different languages can be used for improving the performance of a monolingual semantic parser. We extend two existing monolingual semantic parsers to incorporate such cross-lingual distributed logical representations as features. Experiments show that our proposed approach is able to yield improved semantic parsing results on the standard multilingual GeoQuery dataset."
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%0 Conference Proceedings
%T Learning Cross-lingual Distributed Logical Representations for Semantic Parsing
%A Zou, Yanyan
%A Lu, Wei
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F zou-lu-2018-learning
%X With the development of several multilingual datasets used for semantic parsing, recent research efforts have looked into the problem of learning semantic parsers in a multilingual setup. However, how to improve the performance of a monolingual semantic parser for a specific language by leveraging data annotated in different languages remains a research question that is under-explored. In this work, we present a study to show how learning distributed representations of the logical forms from data annotated in different languages can be used for improving the performance of a monolingual semantic parser. We extend two existing monolingual semantic parsers to incorporate such cross-lingual distributed logical representations as features. Experiments show that our proposed approach is able to yield improved semantic parsing results on the standard multilingual GeoQuery dataset.
%R 10.18653/v1/P18-2107
%U https://aclanthology.org/P18-2107/
%U https://doi.org/10.18653/v1/P18-2107
%P 673-679
Markdown (Informal)
[Learning Cross-lingual Distributed Logical Representations for Semantic Parsing](https://aclanthology.org/P18-2107/) (Zou & Lu, ACL 2018)
ACL