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Document-level relation extraction with entity type constraints
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AI
DOI：10.1016/j.neunet.2025.108469.png)
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Abstract
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• Using relation correlations to solve both long-tail and multi-label problems. • Capturing relation correlations with entity type constraints from the global and local perspectives. • Type-constrained graph is constructed in the global perspective. • Type-constrained loss is designed in the local perspective. • Experiments confirm the effectiveness of proposed model in solving long-tail problem and multi-label problem.
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