Named Entity Recognition Applied to Portuguese Texts from the XVIII Century

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dc.contributor.authorZilio, Leonardo
dc.contributor.authorFinatto, Maria
dc.contributor.authorVieira, Renata
dc.date.accessioned2022-06-02T11:10:50Z
dc.date.available2022-06-02T11:10:50Z
dc.date.issued2022-04
dc.description.abstractExtracting data and knowledge dispersed along Portuguese old medical records is important especially for researchers dealing with historical epidemiology and health sciences. An essential task in Natural Language Processing for processing textual information is Named En- tity Recognition (NER). In this paper, our main objective is to test the performance of NER systems for Portuguese for extracting information from XVIII-century medical texts, so that we can provide an annotated version of an important work of this type.por
dc.description.sponsorshipPartially supported by the Portuguese Foundation FCT, under the projects CEECIND/01997/2017 and UIDB/00057/2020.por
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.authoremailrenatav@uevora.pt
dc.identifier.citationZilio, L., Finatto, M.J., Vieira, R.: Named entity recognition applied to portuguese texts from the XVIII century. In: Trojahn, C., Finatto, M.J., de Paiva, V., Vieira, R. (eds.) Proceedings of the Second Workshop on Digital Humanities and Natural Language Processing (2nd DHandNLP 2022) co-located with International Conference on the Computational Processing of Portuguese (PROPOR 2022), Virtual Event, Fortaleza, Brazil, 21st March, 2022. CEUR Workshop Proceedings, vol. 3128, pp. 1–10. CEUR-WS.org (2022), http://ceur-ws.org/Vol-3128/paper10.pdpor
dc.identifier.scientificarea299por
dc.identifier.urihttp://ceur-ws.org/Vol-3128/paper10.pdf
dc.identifier.urihttp://hdl.handle.net/10174/32165
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherCEURpor
dc.rightsopenAccesspor
dc.subjectNamed Entity Recognitionpor
dc.subjectHistorical Medicinepor
dc.titleNamed Entity Recognition Applied to Portuguese Texts from the XVIII Centurypor
dc.typearticlepor

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