Papers with collective entity disambiguation

1 papers
Collective Entity Disambiguation with Structured Gradient Tree Boosting (N18-1)

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Challenge: Existing work on structured gradient tree boosting for collective entity disambiguation is limited to regular classification or regression problems.
Approach: They propose a structured learning model that uses gradient tree boosting to disambiguate named entities in a document.
Outcome: The proposed model outperforms the previous state-of-the-art neural system by near 1% absolute accuracy on the popular AIDA-CoNLL dataset.

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