Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean

TL;DR

Pir'a is the first bilingual Portuguese-English question-answering dataset focused on ocean-related topics, created to support NLP tasks like QA, retrieval, and translation, with 2261 curated QA pairs from diverse sources.

Contribution

It introduces the first Portuguese-English bilingual QA dataset about the ocean, filling a gap in multilingual NLP resources and supporting various NLP tasks.

Findings

First bilingual QA dataset with Portuguese and English.

Contains 2261 curated QA pairs.

Supports multiple NLP tasks including QA and translation.

Abstract

Current research in natural language processing is highly dependent on carefully produced corpora. Most existing resources focus on English; some resources focus on languages such as Chinese and French; few resources deal with more than one language. This paper presents the Pir\'a dataset, a large set of questions and answers about the ocean and the Brazilian coast both in Portuguese and English. Pir\'a is, to the best of our knowledge, the first QA dataset with supporting texts in Portuguese, and, perhaps more importantly, the first bilingual QA dataset that includes this language. The Pir\'a dataset consists of 2261 properly curated question/answer (QA) sets in both languages. The QA sets were manually created based on two corpora: abstracts related to the Brazilian coast and excerpts of United Nation reports about the ocean. The QA sets were validated in a peer-review process with the dataset contributors. We discuss some of the advantages as well as limitations of Pir\'a, as this new resource can support a set of tasks in NLP such as question-answering, information retrieval, and machine translation.