Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru

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Linguistic corpus annotation is one of the most important phases for solving Natural Language Processing (NLP) tasks, as these methods are deeply involved with corpus-based techniques. However, meta-data annotation is a highly laborious manual task. A supportive alternative requires the use of compu...

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Detalles Bibliográficos
Autores: Mercado-Gonzales R., Pereira-Noriega J., Sobrevilla M., Oncevay A.
Formato: objeto de conferencia
Fecha de Publicación:2019
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/547
Enlace del recurso:https://hdl.handle.net/20.500.12390/547
Nivel de acceso:acceso abierto
Materia:Ships
Data mining
Learning algorithms
Learning systems
Natural language processing systems
Agglutinative language
Annotation tool
Computational tools
Corpus annotations
Linguistic annotations
https://purl.org/pe-repo/ocde/ford#6.02.06
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/547
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
title Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
spellingShingle Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
Mercado-Gonzales R.
Ships
Data mining
Learning algorithms
Learning systems
Natural language processing systems
Agglutinative language
Annotation tool
Computational tools
Corpus annotations
Linguistic annotations
https://purl.org/pe-repo/ocde/ford#6.02.06
title_short Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
title_full Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
title_fullStr Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
title_full_unstemmed Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
title_sort Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru
author Mercado-Gonzales R.
author_facet Mercado-Gonzales R.
Pereira-Noriega J.
Sobrevilla M.
Oncevay A.
author_role author
author2 Pereira-Noriega J.
Sobrevilla M.
Oncevay A.
author2_role author
author
author
dc.contributor.author.fl_str_mv Mercado-Gonzales R.
Pereira-Noriega J.
Sobrevilla M.
Oncevay A.
dc.subject.none.fl_str_mv Ships
topic Ships
Data mining
Learning algorithms
Learning systems
Natural language processing systems
Agglutinative language
Annotation tool
Computational tools
Corpus annotations
Linguistic annotations
https://purl.org/pe-repo/ocde/ford#6.02.06
dc.subject.es_PE.fl_str_mv Data mining
Learning algorithms
Learning systems
Natural language processing systems
Agglutinative language
Annotation tool
Computational tools
Corpus annotations
Linguistic annotations
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#6.02.06
description Linguistic corpus annotation is one of the most important phases for solving Natural Language Processing (NLP) tasks, as these methods are deeply involved with corpus-based techniques. However, meta-data annotation is a highly laborious manual task. A supportive alternative requires the use of computational tools. They are likely to simplify some of these operations, while can be adjusted appropriately to the needs of particular language features at the same time. Therefore, this paper presents ChAnot, a web-based annotation tool developed for Peruvian indigenous and highly agglutinative languages, where Shipibo-Konibo was the case study. This new tool is able to support a diverse set of linguistic annotation tasks, such as word segmentation, POS-tag markup, among others. Also, it includes a suggestion engine based on historic and machine learning models, and a set of statistics about previous annotations.
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.isbn.none.fl_str_mv urn:isbn:9791095546009
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/547
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85059897933
identifier_str_mv urn:isbn:9791095546009
2-s2.0-85059897933
url https://hdl.handle.net/20.500.12390/547
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv LREC 2018 - 11th International Conference on Language Resources and Evaluation
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv European Language Resources Association (ELRA)
publisher.none.fl_str_mv European Language Resources Association (ELRA)
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp00954600rp00955600rp00953600rp00952600Mercado-Gonzales R.Pereira-Noriega J.Sobrevilla M.Oncevay A.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2019urn:isbn:9791095546009https://hdl.handle.net/20.500.12390/5472-s2.0-85059897933Linguistic corpus annotation is one of the most important phases for solving Natural Language Processing (NLP) tasks, as these methods are deeply involved with corpus-based techniques. However, meta-data annotation is a highly laborious manual task. A supportive alternative requires the use of computational tools. They are likely to simplify some of these operations, while can be adjusted appropriately to the needs of particular language features at the same time. Therefore, this paper presents ChAnot, a web-based annotation tool developed for Peruvian indigenous and highly agglutinative languages, where Shipibo-Konibo was the case study. This new tool is able to support a diverse set of linguistic annotation tasks, such as word segmentation, POS-tag markup, among others. Also, it includes a suggestion engine based on historic and machine learning models, and a set of statistics about previous annotations.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengEuropean Language Resources Association (ELRA)LREC 2018 - 11th International Conference on Language Resources and Evaluationinfo:eu-repo/semantics/openAccessShipsData mining-1Learning algorithms-1Learning systems-1Natural language processing systems-1Agglutinative language-1Annotation tool-1Computational tools-1Corpus annotations-1Linguistic annotations-1https://purl.org/pe-repo/ocde/ford#6.02.06-1Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peruinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/547oai:repositorio.concytec.gob.pe:20.500.12390/5472024-05-30 15:57:54.523http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d982418d-268c-433b-8175-e6574299e93d"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Chanot: An intelligent annotation tool for indigenous and highly agglutinative languages in Peru</Title> <PublishedIn> <Publication> <Title>LREC 2018 - 11th International Conference on Language Resources and Evaluation</Title> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <SCP-Number>2-s2.0-85059897933</SCP-Number> <ISBN>urn:isbn:9791095546009</ISBN> <Authors> <Author> <DisplayName>Mercado-Gonzales R.</DisplayName> <Person id="rp00954" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Pereira-Noriega J.</DisplayName> <Person id="rp00955" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Sobrevilla M.</DisplayName> <Person id="rp00953" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Oncevay A.</DisplayName> <Person id="rp00952" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>European Language Resources Association (ELRA)</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Ships</Keyword> <Keyword>Data mining</Keyword> <Keyword>Learning algorithms</Keyword> <Keyword>Learning systems</Keyword> <Keyword>Natural language processing systems</Keyword> <Keyword>Agglutinative language</Keyword> <Keyword>Annotation tool</Keyword> <Keyword>Computational tools</Keyword> <Keyword>Corpus annotations</Keyword> <Keyword>Linguistic annotations</Keyword> <Abstract>Linguistic corpus annotation is one of the most important phases for solving Natural Language Processing (NLP) tasks, as these methods are deeply involved with corpus-based techniques. 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