License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.22
URN: urn:nbn:de:0030-drops-145586
URL: https://drops.dagstuhl.de/opus/volltexte/2021/14558/
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Wachowiak, Lennart ; Lang, Christian ; Heinisch, Barbara ; Gromann, Dagmar

Towards Learning Terminological Concept Systems from Multilingual Natural Language Text

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OASIcs-LDK-2021-22.pdf (2 MB)


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.

BibTeX - Entry

@InProceedings{wachowiak_et_al:OASIcs.LDK.2021.22,
  author =	{Wachowiak, Lennart and Lang, Christian and Heinisch, Barbara and Gromann, Dagmar},
  title =	{{Towards Learning Terminological Concept Systems from Multilingual Natural Language Text}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{22:1--22:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14558},
  URN =		{urn:nbn:de:0030-drops-145586},
  doi =		{10.4230/OASIcs.LDK.2021.22},
  annote =	{Keywords: Terminologies, Neural Language Models, Multilingual Information Extraction}
}

Keywords: Terminologies, Neural Language Models, Multilingual Information Extraction
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021
Supplementary Material: Software (Source Code and Dataset): https://github.com/Text2TCS/Towards-Learning-Terminological-Concept-Systems archived at: https://archive.softwareheritage.org/swh:1:dir:fff3183f35a3dd332e1d4a2cdc54d21259b4fae2


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