@inproceedings{cheng-li-2019-zero,
title = "Zero-shot {C}hinese Discourse Dependency Parsing via Cross-lingual Mapping",
author = "Cheng, Yi and
Li, Sujian",
editor = "Balakrishnan, Anusha and
Demberg, Vera and
Khatri, Chandra and
Rastogi, Abhinav and
Scott, Donia and
Walker, Marilyn and
White, Michael",
booktitle = "Proceedings of the 1st Workshop on Discourse Structure in Neural NLG",
month = nov,
year = "2019",
address = "Tokyo, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-8104",
doi = "10.18653/v1/W19-8104",
pages = "24--29",
abstract = "Due to the absence of labeled data, discourse parsing still remains challenging in some languages. In this paper, we present a simple and efficient method to conduct zero-shot Chinese text-level dependency parsing by leveraging English discourse labeled data and parsing techniques. We first construct the Chinese-English mapping from the level of sentence and elementary discourse unit (EDU), and then exploit the parsing results of the corresponding English translations to obtain the discourse trees for the Chinese text. This method can automatically conduct Chinese discourse parsing, with no need of a large scale of Chinese labeled data.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="cheng-li-2019-zero">
<titleInfo>
<title>Zero-shot Chinese Discourse Dependency Parsing via Cross-lingual Mapping</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yi</namePart>
<namePart type="family">Cheng</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sujian</namePart>
<namePart type="family">Li</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2019-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 1st Workshop on Discourse Structure in Neural NLG</title>
</titleInfo>
<name type="personal">
<namePart type="given">Anusha</namePart>
<namePart type="family">Balakrishnan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vera</namePart>
<namePart type="family">Demberg</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Chandra</namePart>
<namePart type="family">Khatri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Abhinav</namePart>
<namePart type="family">Rastogi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<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">Marilyn</namePart>
<namePart type="family">Walker</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">White</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Tokyo, Japan</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Due to the absence of labeled data, discourse parsing still remains challenging in some languages. In this paper, we present a simple and efficient method to conduct zero-shot Chinese text-level dependency parsing by leveraging English discourse labeled data and parsing techniques. We first construct the Chinese-English mapping from the level of sentence and elementary discourse unit (EDU), and then exploit the parsing results of the corresponding English translations to obtain the discourse trees for the Chinese text. This method can automatically conduct Chinese discourse parsing, with no need of a large scale of Chinese labeled data.</abstract>
<identifier type="citekey">cheng-li-2019-zero</identifier>
<identifier type="doi">10.18653/v1/W19-8104</identifier>
<location>
<url>https://aclanthology.org/W19-8104</url>
</location>
<part>
<date>2019-11</date>
<extent unit="page">
<start>24</start>
<end>29</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Zero-shot Chinese Discourse Dependency Parsing via Cross-lingual Mapping
%A Cheng, Yi
%A Li, Sujian
%Y Balakrishnan, Anusha
%Y Demberg, Vera
%Y Khatri, Chandra
%Y Rastogi, Abhinav
%Y Scott, Donia
%Y Walker, Marilyn
%Y White, Michael
%S Proceedings of the 1st Workshop on Discourse Structure in Neural NLG
%D 2019
%8 November
%I Association for Computational Linguistics
%C Tokyo, Japan
%F cheng-li-2019-zero
%X Due to the absence of labeled data, discourse parsing still remains challenging in some languages. In this paper, we present a simple and efficient method to conduct zero-shot Chinese text-level dependency parsing by leveraging English discourse labeled data and parsing techniques. We first construct the Chinese-English mapping from the level of sentence and elementary discourse unit (EDU), and then exploit the parsing results of the corresponding English translations to obtain the discourse trees for the Chinese text. This method can automatically conduct Chinese discourse parsing, with no need of a large scale of Chinese labeled data.
%R 10.18653/v1/W19-8104
%U https://aclanthology.org/W19-8104
%U https://doi.org/10.18653/v1/W19-8104
%P 24-29
Markdown (Informal)
[Zero-shot Chinese Discourse Dependency Parsing via Cross-lingual Mapping](https://aclanthology.org/W19-8104) (Cheng & Li, INLG 2019)
ACL