Papers with relation extraction approaches

2 papers
Discovering Implicit Knowledge with Unary Relations (P18-1)

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Challenge: State-of-the-art relation extraction methods only recognize relationships between mentions of entity arguments stated explicitly in the text.
Approach: They propose a method to identify relations between two entities using unary relations and a common deep learning based representation.
Outcome: The proposed method outperforms state-of-the-art relation extraction technology on a web scale knowledge base population benchmark.
Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas (D19-1)

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Challenge: Existing approaches to extract n-ary relations from text are limited to binary relations.
Approach: They propose to learn relation representations of lower-arity facts from decomposing higher-arities . they conduct experiments with datasets for ternary relation extraction .
Outcome: The proposed method improves the performance of n-ary relation extraction methods compared to previous methods.

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