<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="dranca-2020-multi">
    <titleInfo>
        <title>Multi-Strategy system for translation inference across dictionaries</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Lacramioara</namePart>
        <namePart type="family">Dranca</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <language>
        <languageTerm type="text">English</languageTerm>
        <languageTerm type="code" authority="iso639-2b">eng</languageTerm>
    </language>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2020 Globalex Workshop on Linked Lexicography</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ilan</namePart>
            <namePart type="family">Kernerman</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Simon</namePart>
            <namePart type="family">Krek</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">John</namePart>
            <namePart type="given">P</namePart>
            <namePart type="family">McCrae</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jorge</namePart>
            <namePart type="family">Gracia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sina</namePart>
            <namePart type="family">Ahmadi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Besim</namePart>
            <namePart type="family">Kabashi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>European Language Resources Association</publisher>
            <place>
                <placeTerm type="text">Marseille, France</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-10-95546-46-7</identifier>
    </relatedItem>
    <abstract>This paper describes four different strategies proposed to the TIAD 2020 Shared Task for automatic translation inference across dictionaries. The proposed strategies are based on the analysis of Apertium RDF graph, taking advantage of characteristics such as translation using multiple paths, synonyms and similarities between lexical entries from different lexicons and cardinality of possible translations through the graph. The four strategies were trained and validated on the Apertium RDF EN\textless-\textgreaterES dictionary, showing promising results. Finally, the strategies, applied together, obtained an F-measure of 0.43 in the task of inferring the dictionaries proposed in the shared task, ranking thus third with respect to the other new systems presented to the TIAD 2020 Shared Task. No system presented to the shared task exceeded the baseline proposed by the TIAD organizers.</abstract>
    <identifier type="citekey">dranca-2020-multi</identifier>
    <location>
        <url>https://aclanthology.org/2020.globalex-1.18</url>
    </location>
    <part>
        <date>2020-05</date>
        <extent unit="page">
            <start>111</start>
            <end>115</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Multi-Strategy system for translation inference across dictionaries
%A Dranca, Lacramioara
%Y Kernerman, Ilan
%Y Krek, Simon
%Y McCrae, John P.
%Y Gracia, Jorge
%Y Ahmadi, Sina
%Y Kabashi, Besim
%S Proceedings of the 2020 Globalex Workshop on Linked Lexicography
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-46-7
%G English
%F dranca-2020-multi
%X This paper describes four different strategies proposed to the TIAD 2020 Shared Task for automatic translation inference across dictionaries. The proposed strategies are based on the analysis of Apertium RDF graph, taking advantage of characteristics such as translation using multiple paths, synonyms and similarities between lexical entries from different lexicons and cardinality of possible translations through the graph. The four strategies were trained and validated on the Apertium RDF EN\textless-\textgreaterES dictionary, showing promising results. Finally, the strategies, applied together, obtained an F-measure of 0.43 in the task of inferring the dictionaries proposed in the shared task, ranking thus third with respect to the other new systems presented to the TIAD 2020 Shared Task. No system presented to the shared task exceeded the baseline proposed by the TIAD organizers.
%U https://aclanthology.org/2020.globalex-1.18
%P 111-115

Markdown (Informal)

[Multi-Strategy system for translation inference across dictionaries](https://aclanthology.org/2020.globalex-1.18) (Dranca, GLOBALEX 2020)

• Multi-Strategy system for translation inference across dictionaries (Dranca, GLOBALEX 2020)

ACL

• Lacramioara Dranca. 2020. Multi-Strategy system for translation inference across dictionaries. In Proceedings of the 2020 Globalex Workshop on Linked Lexicography, pages 111–115, Marseille, France. European Language Resources Association.