Papers with symmetrical expanding path

1 papers
RelU-Net: Syntax-aware Graph U-Net for Relational Triple Extraction (2022.emnlp-main)

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Challenge: Existing methods focused on capturing semantic information but failed to incorporate syntactic structures of the sentence, which is proved to contain rich relational information.
Approach: They propose a framework to capture syntactic information for relational triple extraction by contracting dependency tree into a core relational topology and eliminating redundant information with graph pooling operations.
Outcome: The proposed framework incorporates syntactic information for relational triple extraction.

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