End-to-End Neural Bridging Resolution

Hideo Kobayashi; Yufang Hou; Vincent Ng

End-to-End Neural Bridging Resolution

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Abstract

The state of bridging resolution research is rather unsatisfactory: not only are state-of-the-art resolvers evaluated in unrealistic settings, but the neural models underlying these resolvers are weaker than those used for entity coreference resolution. In light of these problems, we evaluate bridging resolvers in an end-to-end setting, strengthen them with better encoders, and attempt to gain a better understanding of them via perturbation experiments and a manual analysis of their outputs.

Anthology ID:: 2022.coling-1.64
Volume:: Proceedings of the 29th International Conference on Computational Linguistics
Month:: October
Year:: 2022
Address:: Gyeongju, Republic of Korea
Editors:: Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
Venue:: COLING
SIG:
Publisher:: International Committee on Computational Linguistics
Note:
Pages:: 766–778
Language:
URL:: https://aclanthology.org/2022.coling-1.64/
DOI:
Bibkey:
Cite (ACL):: Hideo Kobayashi, Yufang Hou, and Vincent Ng. 2022. End-to-End Neural Bridging Resolution. In Proceedings of the 29th International Conference on Computational Linguistics, pages 766–778, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):: End-to-End Neural Bridging Resolution (Kobayashi et al., COLING 2022)
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PDF:: https://aclanthology.org/2022.coling-1.64.pdf

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@inproceedings{kobayashi-etal-2022-end,
    title = "End-to-End Neural Bridging Resolution",
    author = "Kobayashi, Hideo  and
      Hou, Yufang  and
      Ng, Vincent",
    editor = "Calzolari, Nicoletta  and
      Huang, Chu-Ren  and
      Kim, Hansaem  and
      Pustejovsky, James  and
      Wanner, Leo  and
      Choi, Key-Sun  and
      Ryu, Pum-Mo  and
      Chen, Hsin-Hsi  and
      Donatelli, Lucia  and
      Ji, Heng  and
      Kurohashi, Sadao  and
      Paggio, Patrizia  and
      Xue, Nianwen  and
      Kim, Seokhwan  and
      Hahm, Younggyun  and
      He, Zhong  and
      Lee, Tony Kyungil  and
      Santus, Enrico  and
      Bond, Francis  and
      Na, Seung-Hoon",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.64/",
    pages = "766--778",
    abstract = "The state of bridging resolution research is rather unsatisfactory: not only are state-of-the-art resolvers evaluated in unrealistic settings, but the neural models underlying these resolvers are weaker than those used for entity coreference resolution. In light of these problems, we evaluate bridging resolvers in an end-to-end setting, strengthen them with better encoders, and attempt to gain a better understanding of them via perturbation experiments and a manual analysis of their outputs."
}

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%0 Conference Proceedings
%T End-to-End Neural Bridging Resolution
%A Kobayashi, Hideo
%A Hou, Yufang
%A Ng, Vincent
%Y Calzolari, Nicoletta
%Y Huang, Chu-Ren
%Y Kim, Hansaem
%Y Pustejovsky, James
%Y Wanner, Leo
%Y Choi, Key-Sun
%Y Ryu, Pum-Mo
%Y Chen, Hsin-Hsi
%Y Donatelli, Lucia
%Y Ji, Heng
%Y Kurohashi, Sadao
%Y Paggio, Patrizia
%Y Xue, Nianwen
%Y Kim, Seokhwan
%Y Hahm, Younggyun
%Y He, Zhong
%Y Lee, Tony Kyungil
%Y Santus, Enrico
%Y Bond, Francis
%Y Na, Seung-Hoon
%S Proceedings of the 29th International Conference on Computational Linguistics
%D 2022
%8 October
%I International Committee on Computational Linguistics
%C Gyeongju, Republic of Korea
%F kobayashi-etal-2022-end
%X The state of bridging resolution research is rather unsatisfactory: not only are state-of-the-art resolvers evaluated in unrealistic settings, but the neural models underlying these resolvers are weaker than those used for entity coreference resolution. In light of these problems, we evaluate bridging resolvers in an end-to-end setting, strengthen them with better encoders, and attempt to gain a better understanding of them via perturbation experiments and a manual analysis of their outputs.
%U https://aclanthology.org/2022.coling-1.64/
%P 766-778

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Markdown (Informal)

[End-to-End Neural Bridging Resolution](https://aclanthology.org/2022.coling-1.64/) (Kobayashi et al., COLING 2022)

End-to-End Neural Bridging Resolution (Kobayashi et al., COLING 2022)

ACL

Hideo Kobayashi, Yufang Hou, and Vincent Ng. 2022. End-to-End Neural Bridging Resolution. In Proceedings of the 29th International Conference on Computational Linguistics, pages 766–778, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.