Document-level relation extraction with additional evidence and entity type information
Date
2024
Authors
Li, J.
Wang, J.
Li, C.
Liu, X.
Feng, Z.
Qin, L.
Mayer, W.
Editors
Huang, D.-S.
Si, Z.
Zhang, C.
Si, Z.
Zhang, C.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2024 / Huang, D.-S., Si, Z., Zhang, C. (ed./s), vol.3, pp.226-237
Statement of Responsibility
Conference Name
20th International Conference on Intelligent Computing, ICIC 2024 (5 Aug 2024 - 8 Aug 2024 : Tianjin)
Abstract
Document-level relation extraction faces the challenges of longer text and more complex context than sentence-level relation extraction. In document-level relation extraction, the relation information of an entity pair is usually contained within one or several sentences. However, excessively long document text may lead the model to focus on irrelevant sentences containing wrong information. On the other hand, using only textual information for relation extraction may not be sufficient, some previous models used only text information for relation extraction, ignoring some features of entities themselves, such as entity types, which can be guidance to relation extraction.
To address these issues, a Sentence-Token Attention (STA) layer is developed to integrate sentence-level information into tokens. With a supervised attention optimization, the STA layer enables entities to focus more on relevant sentences. After that, we use an evidence fusion method to fuse the sentence information with context embedding. In addition, we indirectly incorporate the entity type information into the entity embedding as guidance to relation classification. Compared with different models, it is found that our model performs better in both relation extraction and evidence retrieval tasks than previous works.
School/Discipline
Dissertation Note
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Description
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Copyright 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.