Papers by Nicolas Fauceglia

1 papers
Learning Relational Representations by Analogy using Hierarchical Siamese Networks (N19-1)

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Challenge: Existing approaches to learn representations of relations by textual mentions require a large amount of examples for each relation to reach satisfactory performance.
Approach: They propose a method to learn representations of relations expressed by their textual mentions by matching triples in knowledge bases with web-scale corpora through distant supervision.
Outcome: The proposed approach outperforms the state-of-the-art methods on a relation extraction task.

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