<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kafe-2023-mapping">
    <titleInfo>
        <title>Mapping Wordnets on the Fly with Permanent Sense Keys</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Eric</namePart>
        <namePart type="family">Kafe</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-01</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 12th Global Wordnet Conference</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">German</namePart>
            <namePart type="family">Rigau</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Francis</namePart>
            <namePart type="family">Bond</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Alexandre</namePart>
            <namePart type="family">Rademaker</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Global Wordnet Association</publisher>
            <place>
                <placeTerm type="text">University of the Basque Country, Donostia - San Sebastian, Basque Country</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Most of the major databases on the semantic web have links to Princeton WordNet (PWN) synonym set (synset) identifiers, which differ for each PWN release, and are thus incompatible between versions. On the other hand, both PWN and the more recent Open English Wordnet (OEWN) provide permanent word sense identifiers (the sense keys), which can solve this interoperability problem. We present an algorithm that runs in linear time, to automatically derive a synset mapping between any pair of Wordnet versions that use PWN sense keys. This allows to update old WordNet links, and seamlessly interoperate with newer English Wordnet versions for which no prior mapping exists. By applying the proposed algorithm on the fly, at load time, we combine the Open Multilingual Wordnet (OMW 1.4, which uses old PWN 3.0 identifiers) with OEWN Edition 2021, and obtain almost perfect precision and recall. We compare the results of our approach using respectively synset offsets, versus the Collaborative InterLingual Index (CILI version 1.0) as synset identifiers, and find that the synset offsets perform better than CILI 1.0 in all cases, except a few ties.</abstract>
    <identifier type="citekey">kafe-2023-mapping</identifier>
    <location>
        <url>https://aclanthology.org/2023.gwc-1.8</url>
    </location>
    <part>
        <date>2023-01</date>
        <extent unit="page">
            <start>67</start>
            <end>76</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Mapping Wordnets on the Fly with Permanent Sense Keys
%A Kafe, Eric
%Y Rigau, German
%Y Bond, Francis
%Y Rademaker, Alexandre
%S Proceedings of the 12th Global Wordnet Conference
%D 2023
%8 January
%I Global Wordnet Association
%C University of the Basque Country, Donostia - San Sebastian, Basque Country
%F kafe-2023-mapping
%X Most of the major databases on the semantic web have links to Princeton WordNet (PWN) synonym set (synset) identifiers, which differ for each PWN release, and are thus incompatible between versions. On the other hand, both PWN and the more recent Open English Wordnet (OEWN) provide permanent word sense identifiers (the sense keys), which can solve this interoperability problem. We present an algorithm that runs in linear time, to automatically derive a synset mapping between any pair of Wordnet versions that use PWN sense keys. This allows to update old WordNet links, and seamlessly interoperate with newer English Wordnet versions for which no prior mapping exists. By applying the proposed algorithm on the fly, at load time, we combine the Open Multilingual Wordnet (OMW 1.4, which uses old PWN 3.0 identifiers) with OEWN Edition 2021, and obtain almost perfect precision and recall. We compare the results of our approach using respectively synset offsets, versus the Collaborative InterLingual Index (CILI version 1.0) as synset identifiers, and find that the synset offsets perform better than CILI 1.0 in all cases, except a few ties.
%U https://aclanthology.org/2023.gwc-1.8
%P 67-76

Markdown (Informal)

[Mapping Wordnets on the Fly with Permanent Sense Keys](https://aclanthology.org/2023.gwc-1.8) (Kafe, GWC 2023)

• Mapping Wordnets on the Fly with Permanent Sense Keys (Kafe, GWC 2023)

ACL

• Eric Kafe. 2023. Mapping Wordnets on the Fly with Permanent Sense Keys. In Proceedings of the 12th Global Wordnet Conference, pages 67–76, University of the Basque Country, Donostia - San Sebastian, Basque Country. Global Wordnet Association.