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Towards Learning Terminological Concept Systems from Multilingual Natural Language Text

Authors Lennart Wachowiak, Christian Lang, Barbara Heinisch, Dagmar Gromann

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Author Details

Lennart Wachowiak
  • Centre for Translation Studies, University of Vienna, Austria
Christian Lang
  • Centre for Translation Studies, University of Vienna, Austria
Barbara Heinisch
  • Centre for Translation Studies, University of Vienna, Austria
Dagmar Gromann
  • Centre for Translation Studies, University of Vienna, Austria

Funding

This research has been conducted within the Text2TCS project (https://text2tcs.univie.ac.at/) funded by European Language Grid (ELG) H2020 No. 825627.

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Lennart Wachowiak, Christian Lang, Barbara Heinisch, and Dagmar Gromann. Towards Learning Terminological Concept Systems from Multilingual Natural Language Text. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.LDK.2021.22

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.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Information extraction
  • Computing methodologies → Neural networks
  • Computing methodologies → Language resources
Keywords
  • Terminologies
  • Neural Language Models
  • Multilingual Information Extraction

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Supplementary Materials

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