Related Named Entities Classification in the Economic-Financial Context
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/29885 |
Resumo: | The present work uses the Bidirectional Encoder Representations from Transformers(BERT) to process a sentence and its entities and indicate whether two named entities present in a sentence are related or not, constituting a binary classification problem. It was developed for the Portuguese language, considering the financial domain and exploring deep linguistic representations to identify a relation between entities without using other lexical-semantic resources. The results of the experiments show an accuracy of 86% of the predictions. |
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Related Named Entities Classification in the Economic-Financial ContextNamed EntitiesInformation ExtractionThe present work uses the Bidirectional Encoder Representations from Transformers(BERT) to process a sentence and its entities and indicate whether two named entities present in a sentence are related or not, constituting a binary classification problem. It was developed for the Portuguese language, considering the financial domain and exploring deep linguistic representations to identify a relation between entities without using other lexical-semantic resources. The results of the experiments show an accuracy of 86% of the predictions.FCT CEECIND/01997/2017, UIDB/00057/2020ACL Anthology2021-06-08T11:02:44Z2021-06-082021-04-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/29885http://hdl.handle.net/10174/29885engDe Los Reyes, D., Barcelos, A., Vieira, R., Manssour, I. Related Named Entities Classification in the Economic-Financial Context. Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation. 2021. ACL Anthology.https://www.aclweb.org/anthology/2021.hackashop-1.0/ndndrenatav@uevora.ptnd498De Los Reyes, DanielBarcelos, AllanVieira, RenataManssour, Isabelinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:26:56Zoai:dspace.uevora.pt:10174/29885Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:19:16.626694Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Related Named Entities Classification in the Economic-Financial Context |
title |
Related Named Entities Classification in the Economic-Financial Context |
spellingShingle |
Related Named Entities Classification in the Economic-Financial Context De Los Reyes, Daniel Named Entities Information Extraction |
title_short |
Related Named Entities Classification in the Economic-Financial Context |
title_full |
Related Named Entities Classification in the Economic-Financial Context |
title_fullStr |
Related Named Entities Classification in the Economic-Financial Context |
title_full_unstemmed |
Related Named Entities Classification in the Economic-Financial Context |
title_sort |
Related Named Entities Classification in the Economic-Financial Context |
author |
De Los Reyes, Daniel |
author_facet |
De Los Reyes, Daniel Barcelos, Allan Vieira, Renata Manssour, Isabel |
author_role |
author |
author2 |
Barcelos, Allan Vieira, Renata Manssour, Isabel |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
De Los Reyes, Daniel Barcelos, Allan Vieira, Renata Manssour, Isabel |
dc.subject.por.fl_str_mv |
Named Entities Information Extraction |
topic |
Named Entities Information Extraction |
description |
The present work uses the Bidirectional Encoder Representations from Transformers(BERT) to process a sentence and its entities and indicate whether two named entities present in a sentence are related or not, constituting a binary classification problem. It was developed for the Portuguese language, considering the financial domain and exploring deep linguistic representations to identify a relation between entities without using other lexical-semantic resources. The results of the experiments show an accuracy of 86% of the predictions. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-08T11:02:44Z 2021-06-08 2021-04-19T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/29885 http://hdl.handle.net/10174/29885 |
url |
http://hdl.handle.net/10174/29885 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
De Los Reyes, D., Barcelos, A., Vieira, R., Manssour, I. Related Named Entities Classification in the Economic-Financial Context. Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation. 2021. ACL Anthology. https://www.aclweb.org/anthology/2021.hackashop-1.0/ nd nd renatav@uevora.pt nd 498 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
ACL Anthology |
publisher.none.fl_str_mv |
ACL Anthology |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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