Publikation: ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
Lade...
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2021
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
ZHANG, Chengzhi, ed., Philipp MAYR, ed., Wei LU, ed., Yi ZHANG, ed.. Extraction and Evaluation of Knowledge Entities from Scientific Documents 2021 Proceedings of the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2021) co-located with JCDL 2021. New York: ACM, 2021, pp. 5-14. CEUR Workshop Proceedings. eISSN 1613-0073
Zusammenfassung
Named entity recognition (NER) is an important task that aims to resolve universal categories of named entities, e.g., persons, locations, organizations, and times. Despite its common and viable use in many use cases, NER is barely applicable in domains where general categories are suboptimal, such as engineering or medicine. To facilitate NER of domain-specific types, we propose ANEA, an automated (named) entity annotator to assist human annotators in creating domain-specific NER corpora for German text collections when given a set of domain-specific texts. In our evaluation, we find that ANEA automatically identifies terms that best represent the texts’ content, identifies groups of coherent terms, and extracts and assigns descriptive labels to these groups, i.e., annotates text datasets into the domain (named) entities.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
information extraction, low-resource languages, named entity recognition, domain-specific texts
Konferenz
2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2021), 30. Sept. 2021 - 30. Sept. 2021, online
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
ZHUKOVA, Anastasia, Felix HAMBORG, Bela GIPP, 2021. ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts. 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2021). online, 30. Sept. 2021 - 30. Sept. 2021. In: ZHANG, Chengzhi, ed., Philipp MAYR, ed., Wei LU, ed., Yi ZHANG, ed.. Extraction and Evaluation of Knowledge Entities from Scientific Documents 2021 Proceedings of the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2021) co-located with JCDL 2021. New York: ACM, 2021, pp. 5-14. CEUR Workshop Proceedings. eISSN 1613-0073BibTex
@inproceedings{Zhukova2021Autom-56902,
year={2021},
title={ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts},
url={http://ceur-ws.org/Vol-3004/},
publisher={ACM},
address={New York},
series={CEUR Workshop Proceedings},
booktitle={Extraction and Evaluation of Knowledge Entities from Scientific Documents 2021 Proceedings of the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2021) co-located with JCDL 2021},
pages={5--14},
editor={Zhang, Chengzhi and Mayr, Philipp and Lu, Wei and Zhang, Yi},
author={Zhukova, Anastasia and Hamborg, Felix and Gipp, Bela}
}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/123456789/56902">
<dc:creator>Gipp, Bela</dc:creator>
<dc:contributor>Gipp, Bela</dc:contributor>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/56902"/>
<dc:contributor>Zhukova, Anastasia</dc:contributor>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dcterms:title>ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts</dcterms:title>
<dcterms:abstract xml:lang="eng">Named entity recognition (NER) is an important task that aims to resolve universal categories of named entities, e.g., persons, locations, organizations, and times. Despite its common and viable use in many use cases, NER is barely applicable in domains where general categories are suboptimal, such as engineering or medicine. To facilitate NER of domain-specific types, we propose ANEA, an automated (named) entity annotator to assist human annotators in creating domain-specific NER corpora for German text collections when given a set of domain-specific texts. In our evaluation, we find that ANEA automatically identifies terms that best represent the texts’ content, identifies groups of coherent terms, and extracts and assigns descriptive labels to these groups, i.e., annotates text datasets into the domain (named) entities.</dcterms:abstract>
<dc:creator>Hamborg, Felix</dc:creator>
<dc:contributor>Hamborg, Felix</dc:contributor>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-17T11:05:48Z</dcterms:available>
<dc:language>eng</dc:language>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dcterms:issued>2021</dcterms:issued>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:rights>terms-of-use</dc:rights>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-17T11:05:48Z</dc:date>
<dc:creator>Zhukova, Anastasia</dc:creator>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
URL der Originalveröffentl.
Prüfdatum der URL
2022-03-17
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
