We present the roadmap and advances in the area of Information Extraction from legal texts within the EU-funded MIREL project (MIning and REasoning with Legal texts). We describe the resources and tools we have developed for Natural Language Processing in the legal domain, i.e., annotated corpora and automated classifiers for Named Entity Recognition and Linking and Argument Mining. Our final objective is to identify arguments, their content and the relations between them in legal text, with a proof-of-concept in judgments of the European Court of Human Rights (ECHR), to finally sup- port reasoning tasks over mined argumentative structures. This representation will arguably be useful for applications like a reading aid, enhanced information retrieval, structured summarization, intelligent search engines or information extraction. All tools and resources are available at https://github.com/PLN-FaMAF/legal-ontology-population and https://github.com/PLN-FaMAF/ArgumentMiningECHR.
@InProceedings{TERUEL18.6, author = {Milagro Teruel ,Cristian Cardellino ,Fernando Cardellino ,Laura Alonso Alemany and Serena Villata}, title = {Legal text processing within the MIREL project }, booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {may}, date = {7-12}, location = {Miyazaki, Japan}, editor = {Georg Rehm and Víctor Rodríguez-Doncel and Julián Moreno-Schneider}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-18-4}, language = {english} }
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