This is OpiSums-PT-AMR, an AMR annotated corpus of opinion texts in Brazilian Portuguese. All sentences come from the OpiSums-PT corpus, which is a corpus created for Opinion Summarization in Brazilian Portuguese by Lopéz et al. (2015).
The corpus is organized in a single file amr-opisums-pt.txt with multiple sentences. Each sentence is separated by a blank line.
Every sentence has a unique ID corresponding to their location in the OpiSums-PT original corpus. The ID has the following format: directory.file.line, in which directory indicates the name of the directory (product) in the original corpus, file indicates the file name within the directory and line indicates the line number within the file.
There is also an indication of the original sentence represented in AMR. An example is shown as follows:
# ::id Fala-Serio-Mae.Documento_24.0
# ::snt Achei o livro um pouco fútil .
(a / achar-02
:ARG0 (e / eu)
:ARG1 (l / livro)
:ARG2 (f / fútil
:degree (u / um-pouco)))
There is also a new-verbs.txt file, which contains a list of verbs that do not exist within the VerboBrasil repository. This is maintained as there may be researchers interested in further enhance this important resource for the Brazilian Portuguese language.
Inácio, M. L. (2021). Sumarização de Opinião com base em Abstract Meaning Representation [Mestrado em ciências de computação e matemática computacional, Universidade de São Paulo]. https://doi.org/10.11606/D.55.2021.tde-13092021-141741
@mastersthesis{Inacio2021,
type = {{Mestrado em ci\^encias de computa\c{c}\~ao e matem\'atica computacional}},
title = {{Sumariza\c{c}\~ao de Opini\~ao com base em Abstract Meaning Representation}},
author = {In{\'a}cio, Marcio Lima},
year = {2021},
month = sep,
publisher = {{Universidade de S\~ao Paulo}},
address = {{S\~ao Carlos}}
}Inácio, M. L., Cabezudo, M. A. S., Ramisch, R., Di Felippo, A., & Pardo, T. A. S. (2022). The AMR-PT corpus and the semantic annotation of challenging sentences from journalistic and opinion texts [Preprint]. https://doi.org/10.1590/1678-460x202255159
@techreport{InacioEtAl2022,
type = {Preprint},
title = {The {{AMR-PT}} Corpus and the Semantic Annotation of Challenging Sentences from Journalistic and Opinion Texts},
author = {In{\'a}cio, Marcio Lima and Cabezudo, Marco Antonio Sobrevilla and Ramisch, Renata and Di Felippo, Ariani and Pardo, Thiago Alexandre Salgueiro},
year = {2022},
month = aug,
doi = {10.1590/1678-460x202255159},
url = {https://preprints.scielo.org/index.php/scielo/preprint/view/4652/version/4928},
urldate = {2022-08-31},
copyright = {All rights reserved}
}López, R., Pardo, T., Avanço, L., Filho, P., Bokan, A., Cardoso, P., Dias, M., Nóbrega, F., Cabezudo, M., Souza, J., Zacarias, A., Seno, E., and Di Felippo, A. (2015). A qualitative analysis of a corpus of opinion summaries based on aspects. In Proceedings of The 9th Linguistic Annotation Workshop, pages 62–71, Denver, Colorado, USA, June. Association for Computational Linguistics.
The authors are grateful to CAPES and USP Research Office for supporting this work. This work is part of the OPINANDO project.