SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction

• URL: http://arxiv.org/abs/2106.01709v1
• Date: Thu, 3 Jun 2021 09:25:44 GMT
• Title: SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction
• Authors: Shuang Zeng, Yuting Wu and Baobao Chang
• Abstract summary: This paper proposes an effective architecture, SIRE, to represent intra- and inter-sentential relations in different ways. Experiments on the public datasets show SIRE outperforms the previous state-of-the-art methods.
• Score: 16.106186007445146
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Document-level relation extraction has attracted much attention in recent years. It is usually formulated as a classification problem that predicts relations for all entity pairs in the document. However, previous works indiscriminately represent intra- and inter-sentential relations in the same way, confounding the different patterns for predicting them. Besides, they create a document graph and use paths between entities on the graph as clues for logical reasoning. However, not all entity pairs can be connected with a path and have the correct logical reasoning paths in their graph. Thus many cases of logical reasoning cannot be covered. This paper proposes an effective architecture, SIRE, to represent intra- and inter-sentential relations in different ways. We design a new and straightforward form of logical reasoning module that can cover more logical reasoning chains. Experiments on the public datasets show SIRE outperforms the previous state-of-the-art methods. Further analysis shows that our predictions are reliable and explainable. Our code is available at https://github.com/DreamInvoker/SIRE.

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