Papers by Izzeddin Gür

1 papers
Global Relation Embedding for Relation Extraction (N18-1)

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Challenge: Existing methods to extract textual relations with distant supervision are limited by their reliance on supervised training data.
Approach: They propose to embed relations with global statistics of relations to combat the wrong labeling problem of distant supervision.
Outcome: The proposed method is more robust to training noise introduced by distant supervision and improves relation extraction models.

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