Tagging and Labelling Portuguese Modal Verbs

Detalhes bibliográficos
Autor(a) principal: Quaresma, Paulo
Data de Publicação: 2014
Outros Autores: Mendes, Amália, Hendrickx, Iris, Gonçalves, Teresa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/30698
Resumo: We present in this paper an experiment in automatically tagging a set of Portuguese modal verbs with modal information. Modality is the expression of the speaker's (or the subject's) attitude towards the content of the sentences and may be marked with lexical clues such as verbs, adverbs, adjectives, but also by mood and tense. Here we focus exclusively on 9 verbal clues that are frequent in Portuguese and that may have more than one modal meaning. We use as our gold data set a corpus of 160.000 tokens manually annotated, according to a modality annotation scheme for Portuguese. We apply a machine learning approach to predict the modal meaning of a verb in context. This modality tagger takes into consideration all the features available from the parsed data (pos, syntactic and semantic). The results show that the tagger improved the baseline for all verbs, and reached macro-average F-measures between 35 and 81% depending on the modal verb and on the modal value.
id RCAP_4c11c6d90e491e126f90b919953c3139
oai_identifier_str oai:repositorio.ul.pt:10451/30698
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Tagging and Labelling Portuguese Modal VerbsWe present in this paper an experiment in automatically tagging a set of Portuguese modal verbs with modal information. Modality is the expression of the speaker's (or the subject's) attitude towards the content of the sentences and may be marked with lexical clues such as verbs, adverbs, adjectives, but also by mood and tense. Here we focus exclusively on 9 verbal clues that are frequent in Portuguese and that may have more than one modal meaning. We use as our gold data set a corpus of 160.000 tokens manually annotated, according to a modality annotation scheme for Portuguese. We apply a machine learning approach to predict the modal meaning of a verb in context. This modality tagger takes into consideration all the features available from the parsed data (pos, syntactic and semantic). The results show that the tagger improved the baseline for all verbs, and reached macro-average F-measures between 35 and 81% depending on the modal verb and on the modal value.Springer International PublishingRepositório da Universidade de LisboaQuaresma, PauloMendes, AmáliaHendrickx, IrisGonçalves, Teresa2018-01-17T17:02:53Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/30698engQuaresma, Paulo, Amália Mendes, Iris Hendrickx and Teresa Gonçalves (2014) “Tagging and Labelling Portuguese Modal Verbs” in Baptista, Jorge and Nuno Mamede (eds.) PROPOR 2014, LNAI 8775. Springer, Heidelberg, pp. 70-81. ISSN 0302-9743; ISBN 978-3-319-09760-2978-3-319-09760-20302-9743info: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:RCAAP2023-11-08T16:23:36Zoai:repositorio.ul.pt:10451/30698Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:46:19.134650Repositório 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 Tagging and Labelling Portuguese Modal Verbs
title Tagging and Labelling Portuguese Modal Verbs
spellingShingle Tagging and Labelling Portuguese Modal Verbs
Quaresma, Paulo
title_short Tagging and Labelling Portuguese Modal Verbs
title_full Tagging and Labelling Portuguese Modal Verbs
title_fullStr Tagging and Labelling Portuguese Modal Verbs
title_full_unstemmed Tagging and Labelling Portuguese Modal Verbs
title_sort Tagging and Labelling Portuguese Modal Verbs
author Quaresma, Paulo
author_facet Quaresma, Paulo
Mendes, Amália
Hendrickx, Iris
Gonçalves, Teresa
author_role author
author2 Mendes, Amália
Hendrickx, Iris
Gonçalves, Teresa
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Quaresma, Paulo
Mendes, Amália
Hendrickx, Iris
Gonçalves, Teresa
description We present in this paper an experiment in automatically tagging a set of Portuguese modal verbs with modal information. Modality is the expression of the speaker's (or the subject's) attitude towards the content of the sentences and may be marked with lexical clues such as verbs, adverbs, adjectives, but also by mood and tense. Here we focus exclusively on 9 verbal clues that are frequent in Portuguese and that may have more than one modal meaning. We use as our gold data set a corpus of 160.000 tokens manually annotated, according to a modality annotation scheme for Portuguese. We apply a machine learning approach to predict the modal meaning of a verb in context. This modality tagger takes into consideration all the features available from the parsed data (pos, syntactic and semantic). The results show that the tagger improved the baseline for all verbs, and reached macro-average F-measures between 35 and 81% depending on the modal verb and on the modal value.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
2018-01-17T17:02:53Z
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/10451/30698
url http://hdl.handle.net/10451/30698
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Quaresma, Paulo, Amália Mendes, Iris Hendrickx and Teresa Gonçalves (2014) “Tagging and Labelling Portuguese Modal Verbs” in Baptista, Jorge and Nuno Mamede (eds.) PROPOR 2014, LNAI 8775. Springer, Heidelberg, pp. 70-81. ISSN 0302-9743; ISBN 978-3-319-09760-2
978-3-319-09760-2
0302-9743
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.publisher.none.fl_str_mv Springer International Publishing
publisher.none.fl_str_mv Springer International Publishing
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
_version_ 1799134387582795776