Titel
Towards Learning Terminological Concept Systems from Multilingual Natural Language Text
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Abstract
Terminological Concept Systems (TCS) provide a means of organizing, structuring and representing domain-specific multilingual information and are important to ensure terminological consistency in many tasks, such as translation and cross-border communication. While several approaches to (semi-)automatic term extraction exist, learning their interrelations is vastly underexplored. We propose an automated method to extract terms and relations across natural languages and specialized domains. To this end, we adapt pretrained multilingual neural language models, which we evaluate on term extraction standard datasets with best performing results and a combination of relation extraction standard datasets with competitive results. Code and dataset are publicly available.
Stichwort
TerminologiesNeural Language ModelsMultilingual Information Extraction
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:1603855
Enthalten in
Titel
3rd Conference on Language, Data and Knowledge (LDK 2021)
ISBN
978-3-95977-199-3
Reihe
Titel
Open Access Series in Informatics (OASIcs)
Band
93
Verlag
Schloss Dagstuhl - Leibniz-Zentrum für Informatik , 2021
Zugänglichkeit
Rechteangabe
© Lennart Wachowiak, Christian Lang, Barbara Heinisch, and Dagmar Gromann

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