DOI of the published article https://doi.org/10.1590/1678-460x202339355159
The AMR-PT corpus and the semantic annotation of challenging sentences from journalistic and opinion texts
Keywords:corpus annotation, knowledge representation, semantics
One of the most popular semantic representation languages in Natural Language Processing (NLP) is Abstract Meaning Representation (AMR). This formalism encodes the meaning of single sentences in directed rooted graphs. For English, there is a large annotated corpus that provides qualitative and reusable data for building or improving existing NLP methods and applications. For building AMR corpora for non-English languages, including Brazilian Portuguese, automatic and manual strategies have been conducted. The automatic annotation methods are essentially based on the cross-linguistic alignment of parallel corpora and the inheritance of the AMR annotation. The manual strategies focus on adapting the AMR English guidelines to a target language. Both annotation strategies have to deal with some phenomena that are challenging. This paper explores in detail some characteristics of Portuguese for which the AMR model had to be adapted and introduces two annotated corpora: AMRNews, a corpus of 870 annotated sentences from journalistic texts, and OpiSums-PT-AMR, comprising 404 opinionated sentences in AMR.
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Copyright (c) 2022 Marcio Lima Inácio, Marco Antonio Sobrevilla Cabezudo, Renata Ramisch, Ariani Di Felippo, Thiago Alexandre Salgueiro Pardo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Grant numbers PRP #668
Fundação de Amparo à Pesquisa do Estado de São Paulo
Grant numbers 2019/07665-4