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Simple BERT Models for Relation Extraction and Semantic Role Labeling

arXiv 1904.05255 ↗First posted 10 Apr 2019cs.CLcited by 154

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Abstract (arXiv)

We present simple BERT-based models for relation extraction and semantic role labeling. In recent years, state-of-the-art performance has been achieved using neural models by incorporating lexical and syntactic features such as part-of-speech tags and dependency trees. In this paper, extensive experiments on datasets for these two tasks show that without using any external features, a simple BERT-based model can achieve state-of-the-art performance. To our knowledge, we are the first to successfully apply BERT in this manner. Our models provide strong baselines for future research.

Key facts. Cited by 154 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Apr 2019.

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Citing papers per year: 2021: 47; 2022: 40; 2023: 40; 2024: 18; 2025: 5; 2026: 4.

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38 more
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