A Larger Annotated Corpus of Portuguese Coreference

Evandro B. Fonseca; Renata Vieira

A Larger Annotated Corpus of Portuguese Coreference

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Abstract

Coreference resolution is a crucial task in natural language processing (NLP) that aims to identify and link expressions in a text that refer to the same entity. However, the lack of annotated data for coreference resolution in Portuguese has hindered the development of robust and accurate systems for this language. In this paper, we present an assessment of coreference annotation utilizing large language models (LLMs) for Portuguese: LLM-PREF is proposed to annotate coreference in Portuguese texts. It was evaluated and compared to a system previously proposed in the literature. The results show that although the model’s world knowledge and inference capacity are quite rich - allowing it to recognize complex coreference patterns, including the pronominal anaphora phenomenon - it does not excel the previously developed rule based system.

Anthology ID:: 2026.propor-2.33
Volume:: Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2
Month:: April
Year:: 2026
Address:: Salvador, Brazil
Editors:: Marlo Souza, Iria de-Dios-Flores, Diana Santos, Larissa Freitas, Jackson Wilke da Cruz Souza, Eugénio Ribeiro
Venue:: PROPOR
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 247–254
Language:
URL:: https://aclanthology.org/2026.propor-2.33/
DOI:
Bibkey:
Cite (ACL):: Evandro Fonseca and Renata Vieira. 2026. A Larger Annotated Corpus of Portuguese Coreference. In Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2, pages 247–254, Salvador, Brazil. Association for Computational Linguistics.
Cite (Informal):: A Larger Annotated Corpus of Portuguese Coreference (Fonseca & Vieira, PROPOR 2026)
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PDF:: https://aclanthology.org/2026.propor-2.33.pdf

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@inproceedings{fonseca-vieira-2026-larger,
    title = "A Larger Annotated Corpus of {P}ortuguese Coreference",
    author = "Fonseca, Evandro  and
      Vieira, Renata",
    editor = "Souza, Marlo  and
      de-Dios-Flores, Iria  and
      Santos, Diana  and
      Freitas, Larissa  and
      Souza, Jackson Wilke da Cruz  and
      Ribeiro, Eug{\'e}nio",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 2",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.propor-2.33/",
    pages = "247--254",
    ISBN = "979-8-89176-387-6",
    abstract = "Coreference resolution is a crucial task in natural language processing (NLP) that aims to identify and link expressions in a text that refer to the same entity. However, the lack of annotated data for coreference resolution in Portuguese has hindered the development of robust and accurate systems for this language. In this paper, we present an assessment of coreference annotation utilizing large language models (LLMs) for Portuguese: LLM-PREF is proposed to annotate coreference in Portuguese texts. It was evaluated and compared to a system previously proposed in the literature. The results show that although the model{'}s world knowledge and inference capacity are quite rich - allowing it to recognize complex coreference patterns, including the pronominal anaphora phenomenon - it does not excel the previously developed rule based system."
}

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%0 Conference Proceedings
%T A Larger Annotated Corpus of Portuguese Coreference
%A Fonseca, Evandro
%A Vieira, Renata
%Y Souza, Marlo
%Y de-Dios-Flores, Iria
%Y Santos, Diana
%Y Freitas, Larissa
%Y Souza, Jackson Wilke da Cruz
%Y Ribeiro, Eugénio
%S Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2
%D 2026
%8 April
%I Association for Computational Linguistics
%C Salvador, Brazil
%@ 979-8-89176-387-6
%F fonseca-vieira-2026-larger
%X Coreference resolution is a crucial task in natural language processing (NLP) that aims to identify and link expressions in a text that refer to the same entity. However, the lack of annotated data for coreference resolution in Portuguese has hindered the development of robust and accurate systems for this language. In this paper, we present an assessment of coreference annotation utilizing large language models (LLMs) for Portuguese: LLM-PREF is proposed to annotate coreference in Portuguese texts. It was evaluated and compared to a system previously proposed in the literature. The results show that although the model’s world knowledge and inference capacity are quite rich - allowing it to recognize complex coreference patterns, including the pronominal anaphora phenomenon - it does not excel the previously developed rule based system.
%U https://aclanthology.org/2026.propor-2.33/
%P 247-254

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Markdown (Informal)

[A Larger Annotated Corpus of Portuguese Coreference](https://aclanthology.org/2026.propor-2.33/) (Fonseca & Vieira, PROPOR 2026)

A Larger Annotated Corpus of Portuguese Coreference (Fonseca & Vieira, PROPOR 2026)

ACL

Evandro Fonseca and Renata Vieira. 2026. A Larger Annotated Corpus of Portuguese Coreference. In Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 2, pages 247–254, Salvador, Brazil. Association for Computational Linguistics.