DROPS

Document

DOI: 10.4230/OASIcs.LDK.2021.24

Universal Dependencies for Multilingual Open Information Extraction

Authors: Massinissa Atmani and Mathieu Lafourcade

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract

In this paper, we present our approach for Multilingual Open Information Extraction. Our sequence labeling based approach builds only on Universal Dependency representation to capture OpenIE’s regularities and to perform Cross-lingual Multilingual OpenIE. We propose a new two-stage pipeline model for sequence labeling, that first identifies all the arguments of the relation and only then classifies them according to their most likely label. This paper also introduces a new benchmark evaluation for French. Experimental Evaluation shows that our approach achieves the best results in the available Benchmarks (English, French, Spanish and Portuguese).

Cite as

Massinissa Atmani and Mathieu Lafourcade. Universal Dependencies for Multilingual Open Information Extraction. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 24:1-24:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{atmani_et_al:OASIcs.LDK.2021.24,
  author =	{Atmani, Massinissa and Lafourcade, Mathieu},
  title =	{{Universal Dependencies for Multilingual Open Information Extraction}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{24:1--24:15},
  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/entities/document/10.4230/OASIcs.LDK.2021.24},
  URN =		{urn:nbn:de:0030-drops-145600},
  doi =		{10.4230/OASIcs.LDK.2021.24},
  annote =	{Keywords: Natural Language Processing, Information Extraction, Machine Learning}
}

Search Results

Documents authored by Atmani, Massinissa

Universal Dependencies for Multilingual Open Information Extraction

Abstract

Cite as

Thanks for your feedback!

Could not send message