@inproceedings{oliveira-rodrigues-2026-annotated,
title = "From Annotated Clinical Narratives to Ontology: Structuring {B}razilian {P}ortuguese Clinical Data",
author = "Oliveira, Fernando Henrique Moura de and
Rodrigues, Cleyton M{\'a}rio de Oliveira",
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-2.20/",
pages = "128--134",
ISBN = "979-8-89176-387-6",
abstract = "Clinical NLP for Brazilian Portuguese remains limited by the lack of semantically structured resources that support interoperability and downstream health applications. Although existing corpora provide annotated clinical narratives, their flat annotation schemes restrict semantic expressiveness and alignment with standardized terminologies. In this work, we present a lightweight domain ontology that models clinical entities, contextual qualifiers, and semantic relations in Brazilian Portuguese texts. The ontology is derived from the original corpus annotations and conceptually aligned with standards to enhance interoperability while preserving corpus-specific semantics. This work establishes foundational infrastructure for Portuguese clinical NLP, supporting tasks such as entity normalization, semantic search, and ontology-guided annotation."
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<abstract>Clinical NLP for Brazilian Portuguese remains limited by the lack of semantically structured resources that support interoperability and downstream health applications. Although existing corpora provide annotated clinical narratives, their flat annotation schemes restrict semantic expressiveness and alignment with standardized terminologies. In this work, we present a lightweight domain ontology that models clinical entities, contextual qualifiers, and semantic relations in Brazilian Portuguese texts. The ontology is derived from the original corpus annotations and conceptually aligned with standards to enhance interoperability while preserving corpus-specific semantics. This work establishes foundational infrastructure for Portuguese clinical NLP, supporting tasks such as entity normalization, semantic search, and ontology-guided annotation.</abstract>
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%0 Conference Proceedings
%T From Annotated Clinical Narratives to Ontology: Structuring Brazilian Portuguese Clinical Data
%A Oliveira, Fernando Henrique Moura de
%A Rodrigues, Cleyton Mário de Oliveira
%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 oliveira-rodrigues-2026-annotated
%X Clinical NLP for Brazilian Portuguese remains limited by the lack of semantically structured resources that support interoperability and downstream health applications. Although existing corpora provide annotated clinical narratives, their flat annotation schemes restrict semantic expressiveness and alignment with standardized terminologies. In this work, we present a lightweight domain ontology that models clinical entities, contextual qualifiers, and semantic relations in Brazilian Portuguese texts. The ontology is derived from the original corpus annotations and conceptually aligned with standards to enhance interoperability while preserving corpus-specific semantics. This work establishes foundational infrastructure for Portuguese clinical NLP, supporting tasks such as entity normalization, semantic search, and ontology-guided annotation.
%U https://aclanthology.org/2026.propor-2.20/
%P 128-134
Markdown (Informal)
[From Annotated Clinical Narratives to Ontology: Structuring Brazilian Portuguese Clinical Data](https://aclanthology.org/2026.propor-2.20/) (Oliveira & Rodrigues, PROPOR 2026)
ACL