@inproceedings{fernandes-etal-2025-enhancing,
title = "The Incremental Process of Building an Annotation Scheme for Clinical Narratives in {P}ortuguese: the Contribution of Human Variation Analysis",
author = "Fernandes, Ana Lu{\'i}sa and
Silvano, Purifica{\c{c}}{\~a}o and
Leal, Ant{\'o}nio and
Guimar{\~a}es, Nuno and
Rb-Silva, Rita and
Cunha, Lu{\'i}s Filipe and
Jorge, Al{\'i}pio",
editor = "Peng, Siyao and
Rehbein, Ines",
booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.law-1.28/",
doi = "10.18653/v1/2025.law-1.28",
pages = "332--343",
ISBN = "979-8-89176-262-6",
abstract = "The development of a robust annotation scheme and corresponding guidelines is crucial for producing annotated datasets that advance both linguistic and computational research. This paper presents a case study that outlines a methodology for designing an annotation scheme and its guidelines, specifically aimed at representing morphosyntactic and semantic information regarding temporal features, as well as medical information in medical reports written in Portuguese. We detail a multi-step process that includes reviewing existing frameworks, conducting an annotation experiment to determine the optimal approach, and designing a model based on these findings. We validated the approach through a pilot experiment where we assessed the reliability and applicability of the annotation scheme and guidelines. In this experiment, two annotators independently annotated a patient{'}s medical report consisting of six documents using the proposed model, while a curator established the ground truth. The analysis of inter-annotator agreement and the annotation results enabled the identification of sources of human variation and provided insights for further refinement of the annotation scheme and guidelines."
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%0 Conference Proceedings
%T The Incremental Process of Building an Annotation Scheme for Clinical Narratives in Portuguese: the Contribution of Human Variation Analysis
%A Fernandes, Ana Luísa
%A Silvano, Purificação
%A Leal, António
%A Guimarães, Nuno
%A Rb-Silva, Rita
%A Cunha, Luís Filipe
%A Jorge, Alípio
%Y Peng, Siyao
%Y Rehbein, Ines
%S Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-262-6
%F fernandes-etal-2025-enhancing
%X The development of a robust annotation scheme and corresponding guidelines is crucial for producing annotated datasets that advance both linguistic and computational research. This paper presents a case study that outlines a methodology for designing an annotation scheme and its guidelines, specifically aimed at representing morphosyntactic and semantic information regarding temporal features, as well as medical information in medical reports written in Portuguese. We detail a multi-step process that includes reviewing existing frameworks, conducting an annotation experiment to determine the optimal approach, and designing a model based on these findings. We validated the approach through a pilot experiment where we assessed the reliability and applicability of the annotation scheme and guidelines. In this experiment, two annotators independently annotated a patient’s medical report consisting of six documents using the proposed model, while a curator established the ground truth. The analysis of inter-annotator agreement and the annotation results enabled the identification of sources of human variation and provided insights for further refinement of the annotation scheme and guidelines.
%R 10.18653/v1/2025.law-1.28
%U https://aclanthology.org/2025.law-1.28/
%U https://doi.org/10.18653/v1/2025.law-1.28
%P 332-343
Markdown (Informal)
[The Incremental Process of Building an Annotation Scheme for Clinical Narratives in Portuguese: the Contribution of Human Variation Analysis](https://aclanthology.org/2025.law-1.28/) (Fernandes et al., LAW 2025)
ACL