Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/140137 |
Resumo: | This study reflects all stages of the application of BERT for an Extractive Question Answering task applied to the domain of the Portuguese Retirement Law, from data curation through testing. Additionally, it aims to answer whether or not the effort of creating training labels and training the model is justifiable. This is assessed by measuring the performance of the trained model in comparison with that of the base model, which is only pre-trained in the Portuguese language. Since question answering accuracy improved significantly, training is deemed a crucial step to obtain state-of-the-art performance. Generally, the project showed that a BERT model is appropriate to address Extractive Question Answering on the Portuguese Retirement Law domain. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answersMachine learningBusiness analyticsNlpBertHaystackQuestion answeringBert reader trainingBusiness analysisDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis study reflects all stages of the application of BERT for an Extractive Question Answering task applied to the domain of the Portuguese Retirement Law, from data curation through testing. Additionally, it aims to answer whether or not the effort of creating training labels and training the model is justifiable. This is assessed by measuring the performance of the trained model in comparison with that of the base model, which is only pre-trained in the Portuguese language. Since question answering accuracy improved significantly, training is deemed a crucial step to obtain state-of-the-art performance. Generally, the project showed that a BERT model is appropriate to address Extractive Question Answering on the Portuguese Retirement Law domain.Xufre, PatríciaMagalhães, JoãoRUNFigueiral, Ângelo Pascoal2022-06-17T10:29:33Z2022-01-202021-12-172022-01-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/140137TID:202972100enginfo: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:RCAAP2024-03-11T05:17:12Zoai:run.unl.pt:10362/140137Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:49:34.602205Repositório 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 |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
title |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
spellingShingle |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers Figueiral, Ângelo Pascoal Machine learning Business analytics Nlp Bert Haystack Question answering Bert reader training Business analysis Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
title_full |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
title_fullStr |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
title_full_unstemmed |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
title_sort |
Incm & Novasbe Pbl project - retirement law query systemincm & Novasbe Pbl project - retirement law query system: improving the performance of a bert model applied to Portuguese law by training the model-s reader with domain-specific questions and answers |
author |
Figueiral, Ângelo Pascoal |
author_facet |
Figueiral, Ângelo Pascoal |
author_role |
author |
dc.contributor.none.fl_str_mv |
Xufre, Patrícia Magalhães, João RUN |
dc.contributor.author.fl_str_mv |
Figueiral, Ângelo Pascoal |
dc.subject.por.fl_str_mv |
Machine learning Business analytics Nlp Bert Haystack Question answering Bert reader training Business analysis Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Machine learning Business analytics Nlp Bert Haystack Question answering Bert reader training Business analysis Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
This study reflects all stages of the application of BERT for an Extractive Question Answering task applied to the domain of the Portuguese Retirement Law, from data curation through testing. Additionally, it aims to answer whether or not the effort of creating training labels and training the model is justifiable. This is assessed by measuring the performance of the trained model in comparison with that of the base model, which is only pre-trained in the Portuguese language. Since question answering accuracy improved significantly, training is deemed a crucial step to obtain state-of-the-art performance. Generally, the project showed that a BERT model is appropriate to address Extractive Question Answering on the Portuguese Retirement Law domain. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-17 2022-06-17T10:29:33Z 2022-01-20 2022-01-20T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/140137 TID:202972100 |
url |
http://hdl.handle.net/10362/140137 |
identifier_str_mv |
TID:202972100 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 |
instacron_str |
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 |
repository.mail.fl_str_mv |
|
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1799138094071414784 |