@inproceedings{kobayashi-ng-2020-bridging,
title = "Bridging Resolution: A Survey of the State of the Art",
author = "Kobayashi, Hideo and
Ng, Vincent",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.331/",
doi = "10.18653/v1/2020.coling-main.331",
pages = "3708--3721",
abstract = "Bridging reference resolution is an anaphora resolution task that is arguably more challenging and less studied than entity coreference resolution. Given that significant progress has been made on coreference resolution in recent years, we believe that bridging resolution will receive increasing attention in the NLP community. Nevertheless, progress on bridging resolution is currently hampered in part by the scarcity of large annotated corpora for model training as well as the lack of standardized evaluation protocols. This paper presents a survey of the current state of research on bridging reference resolution and discusses future research directions."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kobayashi-ng-2020-bridging">
<titleInfo>
<title>Bridging Resolution: A Survey of the State of the Art</title>
</titleInfo>
<name type="personal">
<namePart type="given">Hideo</namePart>
<namePart type="family">Kobayashi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vincent</namePart>
<namePart type="family">Ng</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 28th International Conference on Computational Linguistics</title>
</titleInfo>
<name type="personal">
<namePart type="given">Donia</namePart>
<namePart type="family">Scott</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nuria</namePart>
<namePart type="family">Bel</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Chengqing</namePart>
<namePart type="family">Zong</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>International Committee on Computational Linguistics</publisher>
<place>
<placeTerm type="text">Barcelona, Spain (Online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Bridging reference resolution is an anaphora resolution task that is arguably more challenging and less studied than entity coreference resolution. Given that significant progress has been made on coreference resolution in recent years, we believe that bridging resolution will receive increasing attention in the NLP community. Nevertheless, progress on bridging resolution is currently hampered in part by the scarcity of large annotated corpora for model training as well as the lack of standardized evaluation protocols. This paper presents a survey of the current state of research on bridging reference resolution and discusses future research directions.</abstract>
<identifier type="citekey">kobayashi-ng-2020-bridging</identifier>
<identifier type="doi">10.18653/v1/2020.coling-main.331</identifier>
<location>
<url>https://aclanthology.org/2020.coling-main.331/</url>
</location>
<part>
<date>2020-12</date>
<extent unit="page">
<start>3708</start>
<end>3721</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Bridging Resolution: A Survey of the State of the Art
%A Kobayashi, Hideo
%A Ng, Vincent
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F kobayashi-ng-2020-bridging
%X Bridging reference resolution is an anaphora resolution task that is arguably more challenging and less studied than entity coreference resolution. Given that significant progress has been made on coreference resolution in recent years, we believe that bridging resolution will receive increasing attention in the NLP community. Nevertheless, progress on bridging resolution is currently hampered in part by the scarcity of large annotated corpora for model training as well as the lack of standardized evaluation protocols. This paper presents a survey of the current state of research on bridging reference resolution and discusses future research directions.
%R 10.18653/v1/2020.coling-main.331
%U https://aclanthology.org/2020.coling-main.331/
%U https://doi.org/10.18653/v1/2020.coling-main.331
%P 3708-3721
Markdown (Informal)
[Bridging Resolution: A Survey of the State of the Art](https://aclanthology.org/2020.coling-main.331/) (Kobayashi & Ng, COLING 2020)
ACL
- Hideo Kobayashi and Vincent Ng. 2020. Bridging Resolution: A Survey of the State of the Art. In Proceedings of the 28th International Conference on Computational Linguistics, pages 3708–3721, Barcelona, Spain (Online). International Committee on Computational Linguistics.