Papers by Rafael Anchiêta

3 papers
Semantically Inspired AMR Alignment for the Portuguese Language (2020.emnlp-main)

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Challenge: Abstract Meaning Representation (AMR) parsers require alignment between nodes and words of the sentence.
Approach: They propose to use a more semantically matched word-concept pair to align graphs with words in Portuguese . they performed intrinsic and extrinsic evaluations and found it outperforms the English alignment strategies.
Outcome: The proposed method outperforms the existing methods for English and achieves competitive results with a parser designed for the Portuguese language.
Towards AMR-BR: A SemBank for Brazilian Portuguese Language (L18-1)

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Challenge: Abstract Meaning Representation (AMR) is a recent and prominent meaning representation with good acceptance and several applications in the Natural Language Processing area.
Approach: They propose to build an AMR annotated corpus for Brazilian Portuguese using an alignment-based approach.
Outcome: The proposed corpus is based on the Little Prince book, which went into the public domain and explored some language-specific annotation issues.
Puntuguese: A Corpus of Puns in Portuguese with Micro-edits (2024.lrec-main)

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Challenge: Existing corpus of punning humor in Portuguese is unfit for machine learning due to data leakage.
Approach: They propose to use Puntuguese to create a corpus of punning humor in Portuguese that is significantly more difficult to recognize than the previous corpus.
Outcome: The proposed corpus achieves an F1-Score of 68.9% and is significantly more difficult than the previous corpus.

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