Deep Neural Networks for Relation Extraction

• URL: http://arxiv.org/abs/2104.01799v1
• Date: Mon, 5 Apr 2021 07:18:54 GMT
• Title: Deep Neural Networks for Relation Extraction
• Authors: Tapas Nayak
• Abstract summary: We first propose a syntax-focused multi-factor attention network model for finding the relation between two entities. Next, we propose two joint entity and relation extraction frameworks based on encoder-decoder architecture.
• Score: 3.792085040881007
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Relation extraction from text is an important task for automatic knowledge base population. In this thesis, we first propose a syntax-focused multi-factor attention network model for finding the relation between two entities. Next, we propose two joint entity and relation extraction frameworks based on encoder-decoder architecture. Finally, we propose a hierarchical entity graph convolutional network for relation extraction across documents.

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