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Sep 22, 2023 · In this paper, we propose a document-level relation extraction framework with both dynamic pruning mechanism and sentence-level attention.
Relation extraction (RE) has been a fundamental task in natural language processing (NLP) as it identifies semantic relations among entity pairs in texts.
Oct 28, 2023 · Document-level relation extraction (DocRE) involves identifying relations between entities distributed in multiple sentences within a doc-.
Nov 12, 2024 · Document-level Relation Extraction (DocRE) aims to extract relations between entity pairs in a document and poses many challenges as it.
Apr 8, 2024 · Document-level relation extraction (RE) focuses on extracting relations for each entity pair in the same sentence or across different sentences of a document.
Missing: Pruning. | Show results with:Pruning.
Document-level relation extraction (DocRE) involves identifying relations between entities distributed in multiple sentences within a document.
Aug 21, 2023 · In this article, we propose a novel model, SRLR, using Separate Relation Representation and Logical Reasoning considering the indirect relation representation.
In this study, we propose a novel two-stage framework to extract document-level relations based on dynamic graph attention networks, namely TDGAT.
Missing: Pruning. | Show results with:Pruning.
Jul 25, 2024 · Document-level relation extraction (RE) aims to identify the relations between entities throughout an entire document. It needs complex ...
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By combining the proposed two techniques, we propose a simple yet effective relation extraction model, named ATLOP. (Adaptive Thresholding and Localized cOntext ...
Missing: Framework Dynamic