Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021 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 C...
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| creator | Paschoal, André F. A Pirozelli, Paulo Freire, Valdinei Delgado, Karina V Peres, Sarajane M José, Marcos M Nakasato, Flávio Oliveira, André S Brandão, Anarosa A. F Costa, Anna H. R Cozman, Fabio G |
| description | CIKM '21: Proceedings of the 30th ACM International Conference on
Information & Knowledge Management, 2021 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. |
| doi_str_mv | 10.48550/arxiv.2202.02398 |
| format | Article |
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Information & Knowledge Management, 2021 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.</description><identifier>DOI: 10.48550/arxiv.2202.02398</identifier><language>eng</language><subject>Computer Science - Computation and Language</subject><creationdate>2022-02</creationdate><rights>http://creativecommons.org/licenses/by-nc-sa/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2202.02398$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2202.02398$$DView paper in arXiv$$Hfree_for_read</backlink><backlink>$$Uhttps://doi.org/10.1145/3459637.3482012$$DView published paper (Access to full text may be restricted)$$Hfree_for_read</backlink></links><search><creatorcontrib>Paschoal, André F. A</creatorcontrib><creatorcontrib>Pirozelli, Paulo</creatorcontrib><creatorcontrib>Freire, Valdinei</creatorcontrib><creatorcontrib>Delgado, Karina V</creatorcontrib><creatorcontrib>Peres, Sarajane M</creatorcontrib><creatorcontrib>José, Marcos M</creatorcontrib><creatorcontrib>Nakasato, Flávio</creatorcontrib><creatorcontrib>Oliveira, André S</creatorcontrib><creatorcontrib>Brandão, Anarosa A. F</creatorcontrib><creatorcontrib>Costa, Anna H. R</creatorcontrib><creatorcontrib>Cozman, Fabio G</creatorcontrib><title>Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean</title><description>CIKM '21: Proceedings of the 30th ACM International Conference on
Information & Knowledge Management, 2021 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.</description><subject>Computer Science - Computation and Language</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpjYJA0NNAzsTA1NdBPLKrILNMzMjIw0jMwMra04GQIDcgsilFPtFJwVHDKzMnMSy9NzFEIyC8qKU0vTS1O1XXNS8_JLM5QcEksSSxOLVFIyy9SCATKlGTm5-k65hWXpxYBNSkkJuWXliiUZKQq-CenJubxMLCmJeYUp_JCaW4GeTfXEGcPXbAD4guKMnMTiyrjQQ6JBzvEmLAKAOmtPco</recordid><startdate>20220204</startdate><enddate>20220204</enddate><creator>Paschoal, André F. A</creator><creator>Pirozelli, Paulo</creator><creator>Freire, Valdinei</creator><creator>Delgado, Karina V</creator><creator>Peres, Sarajane M</creator><creator>José, Marcos M</creator><creator>Nakasato, Flávio</creator><creator>Oliveira, André S</creator><creator>Brandão, Anarosa A. F</creator><creator>Costa, Anna H. R</creator><creator>Cozman, Fabio G</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20220204</creationdate><title>Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean</title><author>Paschoal, André F. A ; Pirozelli, Paulo ; Freire, Valdinei ; Delgado, Karina V ; Peres, Sarajane M ; José, Marcos M ; Nakasato, Flávio ; Oliveira, André S ; Brandão, Anarosa A. F ; Costa, Anna H. R ; Cozman, Fabio G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2202_023983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Computation and Language</topic><toplevel>online_resources</toplevel><creatorcontrib>Paschoal, André F. A</creatorcontrib><creatorcontrib>Pirozelli, Paulo</creatorcontrib><creatorcontrib>Freire, Valdinei</creatorcontrib><creatorcontrib>Delgado, Karina V</creatorcontrib><creatorcontrib>Peres, Sarajane M</creatorcontrib><creatorcontrib>José, Marcos M</creatorcontrib><creatorcontrib>Nakasato, Flávio</creatorcontrib><creatorcontrib>Oliveira, André S</creatorcontrib><creatorcontrib>Brandão, Anarosa A. F</creatorcontrib><creatorcontrib>Costa, Anna H. R</creatorcontrib><creatorcontrib>Cozman, Fabio G</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Paschoal, André F. A</au><au>Pirozelli, Paulo</au><au>Freire, Valdinei</au><au>Delgado, Karina V</au><au>Peres, Sarajane M</au><au>José, Marcos M</au><au>Nakasato, Flávio</au><au>Oliveira, André S</au><au>Brandão, Anarosa A. F</au><au>Costa, Anna H. R</au><au>Cozman, Fabio G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean</atitle><date>2022-02-04</date><risdate>2022</risdate><abstract>CIKM '21: Proceedings of the 30th ACM International Conference on
Information & Knowledge Management, 2021 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.</abstract><doi>10.48550/arxiv.2202.02398</doi><oa>free_for_read</oa></addata></record> |
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| title | Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean |
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