Enhancing Named Entity Recognition in Portuguese Literary Texts with Adaptive Models

Authors

DOI:

https://doi.org/10.21814/lm.17.1.443

Keywords:

named entity recognition, adaptive pre-training, literature in portuguese

Abstract

We investigate pre-training strategies to enhance Named Entity Recognition (NER) in Portuguese literary texts. We introduce two domain-adaptive models, LitBERT-CRF and LitBERTimbau, built on general-domain language models. We also evaluate transfer learning across domains alongside a general-domain baseline (BERT-CRF). Overall, our findings highlight the efficiency of our strategies and their implications for literary NER tasks. Furthermore, experimental results reveal the adapted and domain-specific models outperform the generic baseline with an F1 score of over 75% in a strict evaluation scenario and over 80\% in a partial scenario.

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Published

2025-06-30

Issue

Vol. 17 No. 1

Section

PROPOR 2024 | Invited Articles

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How to Cite

Enhancing Named Entity Recognition in Portuguese Literary Texts with Adaptive Models. (2025). Linguamática, 17(1), 77-94. https://doi.org/10.21814/lm.17.1.443