LREC 2010 - International Conference on Language Resources and Evaluation, La Valetta, Malta, May 2010
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Year 2020 : 5 citations
Alves, D., Kuculo, T., Amaral, G., Thakkar, G., and Tadic, M. (2020). Uner: Universal named-entity recognition framework. In Proceedings of 1st International Workshop on Cross-lingual Event-centric Open Analytics, co-located with 17th Extended Semantic Web Conference (ESWC 2020), CLEOPATRA 2020, pages 72–79. CEUR-WS.org.
Alves, D., Bekavac, B., and Tadic, M. (2020). Optimization of Portuguese Named Entity Recognition and classification by combining local grammars and Conditional Random Fields trained with parsed corpora. In Book of Abstract of the 14th International Conference NooJ 2020, pages 30–31. FF Press.
V. Mendonça, A. Sardinha, L. Coheur and A. L. Santos, "Query Strategies, Assemble! Active Learning with Expert Advice for Low-resource Natural Language Processing," 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, United Kingdom, 2020, pp. 1-8, doi: 10.1109/FUZZ48607.2020.9177707.
da Silva, C. J. A. P. (2020). Detecting and protecting personally identifiable information through machine learning techniques. Master’s thesis, Universidade do Porto.
de Araujo, P. H. L. (2020). From documents to entities: A journey through natural language processing tasks and domains. Master’s thesis, University of Brasília.
Year 2019 : 7 citations
Souza, F., Nogueira, R., and Lotufo, R. (2019). Portuguese named entity recognition using BERT-CRF. arXiv.
Canosa, X., Gamallo, P., Varela, X., Taboada, J. A., Taboada, J. A., and Garcia, M. (2019). Uma utilidade para o reconhecimento de topónimos em documentos medievais. Linguamática, 11(1).
Martin-Rodilla, P., Hattori, M. L., and Gonzalez-Perez, C. (2019). Assisting forensic identification through unsupervised information extraction of free text autopsy reports: The disappearances cases during the Brazilian military dictatorship. Information, 10(7).
Gamallo, P., Garcia, M., and Martín-Rodilla, P. (2019). NER and Open Information Extraction for Portuguese: Notebook for IberLEF 2019 Portuguese Named Entity Recognition and Relation Extraction tasks. In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2019), co-located with 35th Conference of the Spanish Society for Natural Language Processing (SEPLN 2019), CEUR Workshop Proceedings, pages 457–467, Bilbao, Spain. CEUR-WS.org.
Santos, J., Terra, J., Consoli, B., and Vieira, R. (2019). Multidomain contextual embeddings for Portuguese Named Entity Recognition. In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2019), co-located with 35th Conference of the Spanish Society for Natural Language Processing (SEPLN 2019), CEUR Workshop Proceedings, pages 434–441, Bilbao, Spain. CEUR-WS.org.
Rodrigues, A. X. C. (2019). Referentes por coordenadas e georreferências relativas das entidades geográficas mencionadas na Peregrinação. In XII Congresso da Associação Internacional de Lusitanitas (AIL), volume 1, pages 11–34, Macau.
Menezes, D. S., Savarese, P., and Milidú, R. L. (2019). Building a massive corpus for named entity recognition using free open data sources. CoRR, abs/1908.05758.
Year 2018 : 8 citations
Menezes, D. S. S. (2018). Reconhecimento de entidades mencionadas para o português. Master’s thesis, PUC-Rio.
Fernandes, I. A. D. (2018). A deep learning approach to named entity recognition in portuguese texts. Master’s thesis, Universidade do Porto.
de Araujo, P. H. L., de Campos, T. E., de Oliveira, R. R. R., Stauffer, M., Couto, S., and Bermejo, P. (2018). Lener-br: A dataset for named entity recognition in brazilian legal text. In Computational Processing of the Portuguese Language - 13th International Conference, PROPOR 2018, Canela, Brazil, September 24-26, 2018, Proceedings, volume 11122 of LNCS, pages 313–323. Springer.
Cortes, E. G., Woloszyn, V., and Barone, D. A. C. (2018). When, where, who, what or why? a hybrid model to question answering systems. In Computational Processing of the Portuguese Language - 13th International Conference, PROPOR 2018, Canela, Brazil, September 24-26, 2018, Proceedings, volume 11122 of LNCS, pages 136–146. Springer.
Lima, T., Collovini, S., Leal, A. L., Fonseca, E., Han, X., Huang, S., and Vieira, R. (2018). Analysing semantic resources for coreference resolution. In Computational Processing of the Portuguese Language - 13th International Conference, PROPOR 2018, Canela, Brazil, September 24-26, 2018, Proceedings, volume 11122 of LNCS, pages 284–293. Springer.
Fernandes, I., Cardoso, H. L., and Oliveira, E. (2018). Applying deep neural net- works to named entity recognition in portuguese texts. In 5th International Conference on Social Networks Analysis, Management and Security, SNAMS, pages 284–289, Valencia, Spain.
Vieira, R., Mendes, A., Quaresma, P., Fonseca, E., Collovini, S., and Antunes, S. (2018). Corref-pt: A semi-automatic annotated portuguese coreference corpus. Computaci ?on y Systemas, 22(4).
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 : 8 citations
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.
Collovini de Abreu, S. and Vieira, R. (2017). RelP: Portuguese open relation extraction. KO Knowledge Organization, 44(3):163–177.
de Cândido, T. G. and Webber, C. G. (2017). AAACT – avaliador e analisador automático de coesão textual. Technical report, Universidade de Caxias do Sul.
Rocha, G. and Cardoso, H. L. (2017). Coreference resolution in portuguese: The impact of training set generation approaches. In Proceedings of the 12th Doctoral Symposium in Informatics Engineering (DSIE’17), pages 125–136, Porto, Portugal.
Carnaz, G., Bayot, R., Nogueira, V. B., Gonalves, T., and Quaresma, P. (2017). Extracting and representing entities from open sources of information in the agatha project. In Proceedings of the 21th International Conference on Applications of Declarative Programming and Knowledge Man- agement, INAP 2017, Wurzburg, Germany.
Rocha, G. and Cardoso, H. L. (2017). Towards a mention-pair model for coreference resolution in Portuguese. In Progress in Artificial Intelligence - Proceedings of 18th Portuguese Conference on Artificial Intelligence, Porto, Portugal, September 5-8, 2017, LNCS, pages 855–867. Springer.
Fonseca, E., Sesti, V., Collovini, S., Vieira, R., Leal, A. L., and Quaresma, P. (2017). Collective elaboration of a coreference annotated corpus for Portuguese texts. In Proceedings of Evaluation of Human Language Technologies for Iberian Languages, IberEval 2017.
Year 2016 : 5 citations
Antonitsch, A., Figueira, A., Amaral, D., Fonseca, E., Vieira, R., and Collovini, S. (2016). Summ-it++: an enriched version of the summ-it corpus. In Proceedings of 10th International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia. ELRA.
Fonseca, E., Vieira, R., and Vanin, A. (2016). Adapting an entity centric model for portuguese coreference resolution. In Proceedings of 10th International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia. ELRA.
Fonseca, E., Vieira, R., and Vanin, A. (2016). Improving coreference resolution with semantic knowledge. In Proceedings of 12th International Conference on Computational Processing of the Portuguese Language (PROPOR 2016), volume 9727 of LNAI, pages 213–224, Tomar, Portugal. Springer.
Bonatti, R., de Paula, A. G., Lamarca, V. S., and Cozman, F. G. (2016). Effect of part-of-speech and lemmatization filtering in email classification for automatic reply. In Proceedings AAAI-16 Workshop on Knowledge Extraction from Text (KET@AAAI 2016).
Nouvel, D., Ehrmann, M., and Rosset, S. (2016). Named Entities for Computational Linguistics. Wiley-ISTE.
Year 2015 : 6 citations
Chiele, G. C., Fonseca, E., and Vieira, R. (2015). Geração de modelo para reconhecimento de entidades nomeadas no OpenNLP. In IV Student Workshop on Information and Human Language Technology, TILic 2015, pages 15 – 19, Natal, RN, Brasil.
Mendonça Júnior, C., Macedo, H., Bispo, T., Santos, F., Silva, N., and Barbosa, L. (2015). Paramopama: a Brazilian-Portuguese corpus for named entity recognition. In Encontro Nacional de Inteligência Artificial e Computacional, ENIAC 2015, pages 218–223, Natal, RN, Brasil.
Fonseca, E. B., Chiele, G. C., Vieira, R., and Vanin, A. A. (2015). Reconhecimento de entidades nomeadas para o português usando o OpenNLP. In Encontro Nacional de Inteligência Artificial e Computacional, ENIAC 2015, pages 68–72, Natal, RN, Brasil.
Amaral, D. O. F., Buffet, M., and Vieira, R. (2015). Comparative analysis between notations to classify named entities using conditional random fields. In Proceedings of Symposium in Information and Human Language Technology, STIL 2015, pages 27–32, Natal, RN, Brazil.
Bonatti, R. and de Paula, A. G. (2015). Development of email classifier in Brazilian Portuguese using feature selection for automatic response. https://arxiv.org/pdf/1907.04905.pdf.
Evandro B. Fonseca, Renata Vieira, Aline A. Vanin. Dealing With Imbalanced Datasets For Coreference Resolution. Proceedings of the 28th International Florida Artificial Intelligence Research Society Conference (FLAIRS), pp. 169-174. AAAI, 2015.
Year 2014 : 6 citations
Daniela O. F. do Amaral, Evandro Fonseca, Lucelene Lopes, Renata Vieira. Comparing NERP-CRF with Publicly Available Portuguese Named Entities Recognition Tools. Proceedings of International Conference on the Computational Processing of the Portuguese Language (PROPOR 2014), LNCS, Volume 8775, pp 244-249. Springer, 2014.
Evandro B. Fonseca, Renata Vieira, Aline Vanin. Coreference Resolution for Portuguese: Person, Location and Organization. PROPOR 2014 MSc/MA Dissertations contest. São Carlos, SP, Brazil. 2014.
Cristofer Weber and Renata Vieira. Building a Corpus for Named Entity Recognition using Portuguese Wikipedia and DBpedia. Proceedings of the 1st Workshop on Tools and Resources for Automatically Processing Portuguese and Spanish (ToRPorEsp), pp 9-15. São Carlos, SP, Brasil. 2014
Evandro Brasil Fonseca (2014). Resolução de correferências em língua portuguesa: Pessoa, local e organização. Master’s thesis, Pontifícia Universidade Católica do Rio Grande do Sul.
Kaur, Amandeep and Josan, Gurpreet Singh. Improved Named Entity Tagset for Punjabi Language. Proceedings of Recent Advances in Engineering and Computational Sciences (RAECS), pp 1-5, Chandigarh, India. 2014
SANDRA COLLOVINI DE ABREU. Extração de Relações do Domínio de Organizações para o Português. Tese de Doutorado. Pontífica Universidade Católica do Rio Grande do Sul. 2014.
Year 2013 : 2 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
Evandro B. Fonseca and Renata Vieira and Aline A. Vanin. Geração de features para resolução de correferência: Pessoa, Local e Organização. Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology (STIL 2013), pp. 88 -- 97, Fortaleza, Brazil. October 2013.
Year 2012 : 1 citations
Wesley Seidel Carvalho. Reconhecimento de entidades mencionadas em português utilizando aprendizado de máquina. Instituto de Matemática e Estatística da Universidade de São Paulo. 2012.
Year 2011 : 1 citations
Agata Savary and Jakub Piskorski (2011). Language resources for named entity an- notation in the national corpus of polish. Control and Cybernetics, 40(2):361–391.
