cris.boxmetadata.label.title
Towards a general abstract meaning representation corpus for Brazilian Portuguese
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.january 2019
cris.boxmetadata.label.accesslevel
metadata only access
cris.boxmetadata.label.resourcetype
conference paper
cris.boxmetadata.label.authors
University of São Paulo
cris.boxmetadata.label.publisher
Association for Computational Linguistics (ACL)
cris.boxmetadata.label.abstract
Meaning Representation (AMR) is a recent and prominent semantic representation with good acceptance and several applications in the Natural Language Processing area. For English, there is a large annotated corpus (with approximately 39K sentences) that supports the research with the representation. However, to the best of our knowledge, there is only one restricted corpus for Portuguese, which contains 1,527 sentences. In this context, this paper presents an effort to build a general purpose AMR-annotated corpus for Brazilian Portuguese by translating and adapting AMR English guidelines. Our results show that such approach is feasible, but there are some challenging phenomena to solve. More than this, efforts are necessary to increase the coverage of the corresponding lexical resource that supports the annotation.
cris.boxmetadata.label.citationstartpage
236
cris.boxmetadata.label.citationendpage
244
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Lingüística Idiomas específicos
cris.boxmetadata.label.scopusidentifier
2-s2.0-85084314694
cris.boxmetadata.label.partofresource
LAW 2019 - 13th Linguistic Annotation Workshop, Proceedings of the Workshop
cris.boxmetadata.label.containerisbn
9781950737383
cris.boxmetadata.label.conference
13th Linguistic Annotation Workshop, LAW 2019, held in conjunction with the Annual Meeting of the Association for Computational Linguistics, ACL 2019
cris.boxmetadata.label.sponsor
The authors are grateful to CAPES and USP Research Office for supporting this work and to the several corpus annotators that have collaborated with this research.
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