In this paper we describe the first evaluation contest (track) for Portuguese whose goal was to detect and classify relations between named entities in running text, called ReRelEM. Given a collection annotated with named entities belonging to ten different semantic categories, we marked all relationships between them within each document. We used the following fourfold relationship classification: identity, included-in, located-in, and other (which was later on explicitly detailed into twenty different relations). We provide a quantitative description of this evaluation resource, as well as describe the evaluation architecture and summarize the results of the participating systems in the track.
Subject
Natural Language Processing
Conference
SEW-2009 - Semantic Evaluations: Recent Achievements and Future Directions, NAACL-HLT 2009 Workshop, May 2009
Cited by
Year 2020 : 1 citations
Khaldi, H., Abdaoui, A., Benamara, F., Sigel, G., and Aussenac-Gilles, N. (2020). Classification de relations pour l’intelligence ?economique et concurrentielle. In Actes de la 6e conf ?erence conjointe JEP-TALN-RECITAL, Volume 2: Traitement Automatique des Langues Naturelles, pages 27– 39.
Year 2018 : 1 citations
Fonseca, E. B. (2018). Resolução de Correferência Nominal Usando Semântica em Língua Portuguesa. PhD thesis, Pontfícia Universidade Católica do Rio Grande do Sul.
Year 2017 : 4 citations
Lijun, L. (2017). Process-oriented Knowledge Discovery to Support Product Design Using Text Mining. PhD thesis, National University of Singapore.
Fonseca, E., Sesti, V., Antonitsch, A., Vanin, A., and Vieira, R. (2017). CORP: Uma abordagem baseada em regras e conhecimento semntico para a resoluo de correferncias. Linguamática, 9(1):3–18.
Pires, A. R. O. (2017). Named entity extraction from portuguese web text. MSc thesis, Universidade do Porto.
Shi, F., Chen, L., Han, J., and Childs, P. (2017). Implicit knowledge discovery in design semantic network by applying pythagorean means on shortest path searching. In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME.
Year 2016 : 2 citations
Batista, D. S. (2016). Large-Scale Semantic Relationship Extraction for Information Discovery. PhD thesis, Universidade de Lisboa.
Lan, L., Liu, Y., and Lu, W. F. (2016). Discovering a hierarchical design process model using text mining. In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pages V01BT02A024–V01BT02A024. American Society of Mechanical Engineers.
Year 2015 : 1 citations
de Sousa, H. T. (2015). Caracterização de um corpus jornalístico português. Master’s thesis, Universidade do Porto.
Year 2013 : 1 citations
Sandra Collovini de Abreu, Tiago Luis Bonamigo, Renata Vieira. A review on Relation Extraction with an eye on Portuguese. Journal of the Brazilian Computer Society. Springer. July 2013
Year 2012 : 1 citations
Antonio Paulo Santos, Carlos Ramos, Nuno C. Marques. Extração de Relaçoes em Títulos de Notícias Desportivas. Actas do Inforum 2012, Simpósio de Informática, Lisboa, Portugal.
Year 2010 : 2 citations
Daniel Santos, Nuno Mamede and Jorge Baptista: Extraction of Family Relations between Entities. in Proc. of the INFORUM 2010, INFORUM 2010, Braga, Portugal, September 2010
Daniel Tiago de Almeida Santos. "Extracção de Relações entre Entidades". Instituto Superior Técnico, Universidade Técnica de Lisboa 2010.
