@inproceedings{lafourcade-etal-2017-mice,
title = "If mice were reptiles, then reptiles could be mammals or How to detect errors in the {J}eux{D}e{M}ots lexical network?",
author = "Lafourcade, Mathieu and
Joubert, Alain and
Le Brun, Nathalie",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
month = sep,
year = "2017",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://doi.org/10.26615/978-954-452-049-6_056",
doi = "10.26615/978-954-452-049-6_056",
pages = "424--430",
abstract = "Correcting errors in a data set is a critical issue. This task can be either hand-made by experts, or by crowdsourcing methods, or automatically done using algorithms. Although the rate of errors present in the JeuxDeMots network is rather low, it is important to reduce it. We present here automatic methods for detecting potential secondary errors that would result from automatic inference mechanisms when they rely on an initial error manually detected. Encouraging results also invite us to consider strategies that would automatically detect {``}erroneous{''} initial relations, which could lead to the automatic detection of the majority of errors in the network.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="lafourcade-etal-2017-mice">
<titleInfo>
<title>If mice were reptiles, then reptiles could be mammals or How to detect errors in the JeuxDeMots lexical network?</title>
</titleInfo>
<name type="personal">
<namePart type="given">Mathieu</namePart>
<namePart type="family">Lafourcade</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alain</namePart>
<namePart type="family">Joubert</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nathalie</namePart>
<namePart type="family">Le Brun</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2017-09</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ruslan</namePart>
<namePart type="family">Mitkov</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Galia</namePart>
<namePart type="family">Angelova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>INCOMA Ltd.</publisher>
<place>
<placeTerm type="text">Varna, Bulgaria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Correcting errors in a data set is a critical issue. This task can be either hand-made by experts, or by crowdsourcing methods, or automatically done using algorithms. Although the rate of errors present in the JeuxDeMots network is rather low, it is important to reduce it. We present here automatic methods for detecting potential secondary errors that would result from automatic inference mechanisms when they rely on an initial error manually detected. Encouraging results also invite us to consider strategies that would automatically detect “erroneous” initial relations, which could lead to the automatic detection of the majority of errors in the network.</abstract>
<identifier type="citekey">lafourcade-etal-2017-mice</identifier>
<identifier type="doi">10.26615/978-954-452-049-6_056</identifier>
<part>
<date>2017-09</date>
<extent unit="page">
<start>424</start>
<end>430</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T If mice were reptiles, then reptiles could be mammals or How to detect errors in the JeuxDeMots lexical network?
%A Lafourcade, Mathieu
%A Joubert, Alain
%A Le Brun, Nathalie
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F lafourcade-etal-2017-mice
%X Correcting errors in a data set is a critical issue. This task can be either hand-made by experts, or by crowdsourcing methods, or automatically done using algorithms. Although the rate of errors present in the JeuxDeMots network is rather low, it is important to reduce it. We present here automatic methods for detecting potential secondary errors that would result from automatic inference mechanisms when they rely on an initial error manually detected. Encouraging results also invite us to consider strategies that would automatically detect “erroneous” initial relations, which could lead to the automatic detection of the majority of errors in the network.
%R 10.26615/978-954-452-049-6_056
%U https://doi.org/10.26615/978-954-452-049-6_056
%P 424-430
Markdown (Informal)
[If mice were reptiles, then reptiles could be mammals or How to detect errors in the JeuxDeMots lexical network?](https://doi.org/10.26615/978-954-452-049-6_056) (Lafourcade et al., RANLP 2017)
ACL