The AMR-PT corpus and the semantic annotation of challenging sentences from journalistic and opinion texts
Bibliographic Data
| ID | 4768597 |
|---|---|
| Authors | Marcio Lima Inácio (0000-0002-0875-4574, Universidade de Coimbra. Coimbra, Portugal; Universidade de São Paulo, Brasil), Marco Antonio Sobrevilla Cabezudo (0000-0001-7625-9914, Universidade de São Paulo), Renata Ramisch (0000-0003-3372-6150, Redação Nota 1000, Brasil), Ariani Di Felippo (0000-0002-4566-9352, Universidade Federal de São Carlos), Thiago Alexandre Salgueiro Pardo (0000-0003-2111-1319, Universidade de São Paulo) |
| Year | 2023 |
| Volume | 39 |
| Issue | 3 |
| Publication date | 2023-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | DELTA Documentação de Estudos em Lingüística Teórica e Aplicada (JOURNAL) |
| Journal identifiers | ISSN: 0102-4450 • E-ISSN: 1678-460X |
| Publisher | FapUNIFESP (SciELO) (PUBLISHER) |
| DOI | 10.1590/1678-460x202339355159 |
| OpenAlex | W4386832543 |
| SciELO | S0102-44502023000300416 |
| Language | EN |
| References cited | 3 |
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
Annotation · Corpus linguistics · Linguistics · Natural language processing · Portuguese · Representation (politics) · Text corpus · Artificial Intelligence · Computer Science · linguistics and terminology studies · Natural Language Processing Techniques · Topic Modeling
| Highly cited | No |
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