Publikation:

NECKAr : A Named Entity Classifier for Wikidata

Vorschaubild

Dateien

Geiss_2-srmq9b397aes4.pdf
Geiss_2-srmq9b397aes4.pdfGröße: 732.22 KBDownloads: 296

Datum

2018

Autor:innen

Geiß, Johanna
Gertz, Michael

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-srmq9b397aes4
DOI (zitierfähiger Link)
https://doi.org/10.1007/978-3-319-73706-5_10
ArXiv-ID

Internationale Patentnummer

Link zur Lizenz

CC BY 4.0

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Bookpart

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published

Erschienen in

REHM, Georg, ed., Thierry DECLERCK, ed.. Language Technologies for the Challenges of the Digital Age : 27th International Conference, GSCL 2017, Proceedings. Cham: Springer International Publishing, 2018, pp. 115-129. Lecture Notes in Computer Science. 10713. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-73705-8. Available under: doi: 10.1007/978-3-319-73706-5_10

Zusammenfassung

Many Information Extraction tasks such as Named Entity Recognition or Event Detection require background repositories that provide a classification of entities into the basic, predominantly used classes location, person, and organization. Several available knowledge bases offer a very detailed and specific ontology of entities that can be used as a repository. However, due to the mechanisms behind their construction, they are relatively static and of limited use to IE approaches that require up-to-date information. In contrast, Wikidata is a community-edited knowledge base that is kept current by its userbase, but has a constantly evolving and less rigid ontology structure that does not correspond to these basic classes. In this paper we present the tool NECKAr, which assigns Wikidata entities to the three main classes of named entities, as well as the resulting Wikidata NE dataset that consists of over 8 million classified entities. Both are available at http://event.ifi.uni-heidelberg.de/?page_id=532.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Wikidata, Named Entity Classes, Infobox, Wikipedia Language Versions, Wikipedia Categories

Konferenz

GSCL 2017: International Conference of the German Society for Computational Linguistics and Language Technology, 13. Sept. 2017 - 14. Sept. 2017, Berlin, Germany
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Verknüpfte Datensätze

Zitieren

ISO 690GEISS, Johanna, Andreas SPITZ, Michael GERTZ, 2018. NECKAr : A Named Entity Classifier for Wikidata. GSCL 2017: International Conference of the German Society for Computational Linguistics and Language Technology. Berlin, Germany, 13. Sept. 2017 - 14. Sept. 2017. In: REHM, Georg, ed., Thierry DECLERCK, ed.. Language Technologies for the Challenges of the Digital Age : 27th International Conference, GSCL 2017, Proceedings. Cham: Springer International Publishing, 2018, pp. 115-129. Lecture Notes in Computer Science. 10713. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-73705-8. Available under: doi: 10.1007/978-3-319-73706-5_10
BibTex
@inproceedings{Gei2018-01-06NECKA-55799,
  year={2018},
  doi={10.1007/978-3-319-73706-5_10},
  title={NECKAr : A Named Entity Classifier for Wikidata},
  number={10713},
  isbn={978-3-319-73705-8},
  issn={0302-9743},
  publisher={Springer International Publishing},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Language Technologies for the Challenges of the Digital Age : 27th International Conference, GSCL 2017, Proceedings},
  pages={115--129},
  editor={Rehm, Georg and Declerck, Thierry},
  author={Geiß, Johanna and Spitz, Andreas and Gertz, Michael}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/55799">
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:title>NECKAr : A Named Entity Classifier for Wikidata</dcterms:title>
    <dc:creator>Spitz, Andreas</dc:creator>
    <dc:creator>Geiß, Johanna</dc:creator>
    <dc:contributor>Gertz, Michael</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-08T13:10:17Z</dcterms:available>
    <dc:rights>Attribution 4.0 International</dc:rights>
    <dc:contributor>Geiß, Johanna</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55799/1/Geiss_2-srmq9b397aes4.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:issued>2018-01-06</dcterms:issued>
    <dc:creator>Gertz, Michael</dc:creator>
    <dc:contributor>Spitz, Andreas</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55799/1/Geiss_2-srmq9b397aes4.pdf"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/55799"/>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-08T13:10:17Z</dc:date>
    <dcterms:abstract xml:lang="eng">Many Information Extraction tasks such as Named Entity Recognition or Event Detection require background repositories that provide a classification of entities into the basic, predominantly used classes location, person, and organization. Several available knowledge bases offer a very detailed and specific ontology of entities that can be used as a repository. However, due to the mechanisms behind their construction, they are relatively static and of limited use to IE approaches that require up-to-date information. In contrast, Wikidata is a community-edited knowledge base that is kept current by its userbase, but has a constantly evolving and less rigid ontology structure that does not correspond to these basic classes. In this paper we present the tool NECKAr, which assigns Wikidata entities to the three main classes of named entities, as well as the resulting Wikidata NE dataset that consists of over 8 million classified entities. Both are available at http://event.ifi.uni-heidelberg.de/?page_id=532.</dcterms:abstract>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen