ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing

Xinyu Wang; Yixian Liu; Zixia Jia; Chengyue Jiang; Kewei Tu

doi:10.18653/v1/K19-2005

ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing

Xinyu Wang, Yixian Liu, Zixia Jia, Chengyue Jiang, Kewei Tu

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Abstract

This paper presents the system used in our submission to the CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing. Our system is a graph-based parser which combines an extended pointer-generator network that generates nodes and a second-order mean field variational inference module that predicts edges. Our system achieved 1st and 2nd place for the DM and PSD frameworks respectively on the in-framework ranks and achieved 3rd place for the DM framework on the cross-framework ranks.

Anthology ID:: K19-2005
Volume:: Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
Month:: November
Year:: 2019
Address:: Hong Kong
Editors:: Stephan Oepen, Omri Abend, Jan Hajic, Daniel Hershcovich, Marco Kuhlmann, Tim O’Gorman, Nianwen Xue
Venue:: CoNLL
SIG:: SIGNLL
Publisher:: Association for Computational Linguistics
Note:
Pages:: 55–65
Language:
URL:: https://aclanthology.org/K19-2005/
DOI:: 10.18653/v1/K19-2005
Bibkey:
Cite (ACL):: Xinyu Wang, Yixian Liu, Zixia Jia, Chengyue Jiang, and Kewei Tu. 2019. ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, pages 55–65, Hong Kong. Association for Computational Linguistics.
Cite (Informal):: ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing (Wang et al., CoNLL 2019)
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PDF:: https://aclanthology.org/K19-2005.pdf

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@inproceedings{wang-etal-2019-shanghaitech,
    title = "{S}hanghai{T}ech at {MRP} 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing",
    author = "Wang, Xinyu  and
      Liu, Yixian  and
      Jia, Zixia  and
      Jiang, Chengyue  and
      Tu, Kewei",
    editor = "Oepen, Stephan  and
      Abend, Omri  and
      Hajic, Jan  and
      Hershcovich, Daniel  and
      Kuhlmann, Marco  and
      O{'}Gorman, Tim  and
      Xue, Nianwen",
    booktitle = "Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning",
    month = nov,
    year = "2019",
    address = "Hong Kong",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/K19-2005/",
    doi = "10.18653/v1/K19-2005",
    pages = "55--65",
    abstract = "This paper presents the system used in our submission to the CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing. Our system is a graph-based parser which combines an extended pointer-generator network that generates nodes and a second-order mean field variational inference module that predicts edges. Our system achieved 1st and 2nd place for the DM and PSD frameworks respectively on the in-framework ranks and achieved 3rd place for the DM framework on the cross-framework ranks."
}

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%0 Conference Proceedings
%T ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing
%A Wang, Xinyu
%A Liu, Yixian
%A Jia, Zixia
%A Jiang, Chengyue
%A Tu, Kewei
%Y Oepen, Stephan
%Y Abend, Omri
%Y Hajic, Jan
%Y Hershcovich, Daniel
%Y Kuhlmann, Marco
%Y O’Gorman, Tim
%Y Xue, Nianwen
%S Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F wang-etal-2019-shanghaitech
%X This paper presents the system used in our submission to the CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing. Our system is a graph-based parser which combines an extended pointer-generator network that generates nodes and a second-order mean field variational inference module that predicts edges. Our system achieved 1st and 2nd place for the DM and PSD frameworks respectively on the in-framework ranks and achieved 3rd place for the DM framework on the cross-framework ranks.
%R 10.18653/v1/K19-2005
%U https://aclanthology.org/K19-2005/
%U https://doi.org/10.18653/v1/K19-2005
%P 55-65

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Markdown (Informal)

[ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing](https://aclanthology.org/K19-2005/) (Wang et al., CoNLL 2019)

ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing (Wang et al., CoNLL 2019)

ACL

Xinyu Wang, Yixian Liu, Zixia Jia, Chengyue Jiang, and Kewei Tu. 2019. ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, pages 55–65, Hong Kong. Association for Computational Linguistics.