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Multi-perspective context aggregation for document-level relation extraction
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AI
DOI：10.1007/s10489-022-03731-w.png)
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Abstract
En 中文
The task of document-level relation extraction (RE) involves integration of information within and across multiple sentences of a document and extraction of complex semantic relations between multiple named entities. However, effective aggregation of local and nonlocal contexts information in the document continues to be a challenging research question. This study proposes a novel document-level RE model, called the multi-perspective context aggregation (MPCA), that aggregates document context information from multi-perspective at different layers. Specifically, this aggregated context information not only comes from the pre-training stage but is also reflected during node construction and classification. Experimental results show that our model achieves desirable performance on two public datasets for document-level RE and is particularly effective in extracting relations between entities with multiple mentions.
Keywords:
Relation extraction
Document-level
Multi-perspective
Integrate information
Localized context
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