@inproceedings{abdou-etal-2019-x,
title = "{X}-{W}iki{RE}: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension",
author = "Abdou, Mostafa and
Sas, Cezar and
Aralikatte, Rahul and
Augenstein, Isabelle and
S{\o}gaard, Anders",
booktitle = "Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-6130",
doi = "10.18653/v1/D19-6130",
pages = "265--274",
abstract = "Although the vast majority of knowledge bases (KBs) are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduce a new multilingual dataset (X-WikiRE), framing relation extraction as a multilingual machine reading problem. We show that by leveraging this resource it is possible to robustly transfer models cross-lingually and that multilingual support significantly improves (zero-shot) relation extraction, enabling the population of low-resourced KBs from their well-populated counterparts.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="abdou-etal-2019-x">
<titleInfo>
<title>X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension</title>
</titleInfo>
<name type="personal">
<namePart type="given">Mostafa</namePart>
<namePart type="family">Abdou</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Cezar</namePart>
<namePart type="family">Sas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rahul</namePart>
<namePart type="family">Aralikatte</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Isabelle</namePart>
<namePart type="family">Augenstein</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anders</namePart>
<namePart type="family">Søgaard</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 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)</title>
</titleInfo>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Hong Kong, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Although the vast majority of knowledge bases (KBs) are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduce a new multilingual dataset (X-WikiRE), framing relation extraction as a multilingual machine reading problem. We show that by leveraging this resource it is possible to robustly transfer models cross-lingually and that multilingual support significantly improves (zero-shot) relation extraction, enabling the population of low-resourced KBs from their well-populated counterparts.</abstract>
<identifier type="citekey">abdou-etal-2019-x</identifier>
<identifier type="doi">10.18653/v1/D19-6130</identifier>
<location>
<url>https://aclanthology.org/D19-6130</url>
</location>
<part>
<date>2019-11</date>
<extent unit="page">
<start>265</start>
<end>274</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
%A Abdou, Mostafa
%A Sas, Cezar
%A Aralikatte, Rahul
%A Augenstein, Isabelle
%A Søgaard, Anders
%S Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F abdou-etal-2019-x
%X Although the vast majority of knowledge bases (KBs) are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduce a new multilingual dataset (X-WikiRE), framing relation extraction as a multilingual machine reading problem. We show that by leveraging this resource it is possible to robustly transfer models cross-lingually and that multilingual support significantly improves (zero-shot) relation extraction, enabling the population of low-resourced KBs from their well-populated counterparts.
%R 10.18653/v1/D19-6130
%U https://aclanthology.org/D19-6130
%U https://doi.org/10.18653/v1/D19-6130
%P 265-274
Markdown (Informal)
[X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension](https://aclanthology.org/D19-6130) (Abdou et al., 2019)
ACL