@inproceedings{iwata-etal-2021-zero,
title = "Zero Pronouns Identification based on Span prediction",
author = "Iwata, Sei and
Watanabe, Taro and
Nagata, Masaaki",
editor = "Kabbara, Jad and
Lin, Haitao and
Paullada, Amandalynne and
Vamvas, Jannis",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-srw.34/",
doi = "10.18653/v1/2021.acl-srw.34",
pages = "331--336",
abstract = "The presence of zero-pronoun (ZP) greatly affects the downstream tasks of NLP in pro-drop languages such as Japanese and Chinese. To tackle the problem, the previous works identified ZPs as sequence labeling on the word sequence or the linearlized tree nodes of the input. We propose a novel approach to ZP identification by casting it as a query-based argument span prediction task. Given a predicate as a query, our model predicts the omission with ZP. In the experiments, our model surpassed the sequence labeling baseline."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="iwata-etal-2021-zero">
<titleInfo>
<title>Zero Pronouns Identification based on Span prediction</title>
</titleInfo>
<name type="personal">
<namePart type="given">Sei</namePart>
<namePart type="family">Iwata</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Taro</namePart>
<namePart type="family">Watanabe</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Masaaki</namePart>
<namePart type="family">Nagata</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop</title>
</titleInfo>
<name type="personal">
<namePart type="given">Jad</namePart>
<namePart type="family">Kabbara</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Haitao</namePart>
<namePart type="family">Lin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Amandalynne</namePart>
<namePart type="family">Paullada</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jannis</namePart>
<namePart type="family">Vamvas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Online</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>The presence of zero-pronoun (ZP) greatly affects the downstream tasks of NLP in pro-drop languages such as Japanese and Chinese. To tackle the problem, the previous works identified ZPs as sequence labeling on the word sequence or the linearlized tree nodes of the input. We propose a novel approach to ZP identification by casting it as a query-based argument span prediction task. Given a predicate as a query, our model predicts the omission with ZP. In the experiments, our model surpassed the sequence labeling baseline.</abstract>
<identifier type="citekey">iwata-etal-2021-zero</identifier>
<identifier type="doi">10.18653/v1/2021.acl-srw.34</identifier>
<location>
<url>https://aclanthology.org/2021.acl-srw.34/</url>
</location>
<part>
<date>2021-08</date>
<extent unit="page">
<start>331</start>
<end>336</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Zero Pronouns Identification based on Span prediction
%A Iwata, Sei
%A Watanabe, Taro
%A Nagata, Masaaki
%Y Kabbara, Jad
%Y Lin, Haitao
%Y Paullada, Amandalynne
%Y Vamvas, Jannis
%S Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F iwata-etal-2021-zero
%X The presence of zero-pronoun (ZP) greatly affects the downstream tasks of NLP in pro-drop languages such as Japanese and Chinese. To tackle the problem, the previous works identified ZPs as sequence labeling on the word sequence or the linearlized tree nodes of the input. We propose a novel approach to ZP identification by casting it as a query-based argument span prediction task. Given a predicate as a query, our model predicts the omission with ZP. In the experiments, our model surpassed the sequence labeling baseline.
%R 10.18653/v1/2021.acl-srw.34
%U https://aclanthology.org/2021.acl-srw.34/
%U https://doi.org/10.18653/v1/2021.acl-srw.34
%P 331-336
Markdown (Informal)
[Zero Pronouns Identification based on Span prediction](https://aclanthology.org/2021.acl-srw.34/) (Iwata et al., ACL-IJCNLP 2021)
ACL
- Sei Iwata, Taro Watanabe, and Masaaki Nagata. 2021. Zero Pronouns Identification based on Span prediction. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop, pages 331–336, Online. Association for Computational Linguistics.