Two Multilingual Corpora Extracted from the Tenders Electronic Daily for Machine Learning and Machine Translation Applications

Oussama Ahmia (1) , Nicolas Béchet (1) , Pierre-François Marteau (1)

1 EXPRESSION - Expressiveness in Human Centered Data/Media

The European "Tenders Electronic Daily" (TED) is a large source of semi-structured and multilingual data that is very valuable to the Natural Language Processing community. This data sets can effectively be used to address complex machine translation, multilingual terminology extraction, text-mining, or to benchmark information retrieval systems. Despite of the services offered by the user-friendliness of the web site that is made available to the public to access the publishing of the EU call for tenders, collecting and managing such kind of data is a great burden and consumes a lot of time and computing resources. This could explain why such a resource is not very (if any) exploited today by computer scientists or engineers in NLP. The aim of this paper is to describe two documented and easy-to-use multilingual corpora (one of them is a parallel corpus), extracted from the TED web source that we will release for the benefit of the NLP community.

Mots clés: Multilingual corpora; Parallel Corpus; Call for Tender; European Languages; Natural Language Resource

Domaines: Recherche d'information [cs.IR]; Traitement du texte et du document

Oussama Ahmia, Nicolas Béchet, Pierre-François Marteau. Two Multilingual Corpora Extracted from the Tenders Electronic Daily for Machine Learning and Machine Translation Applications. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Myazaki, Japan. ⟨hal-01865091⟩