Learning Distributed Representations of Texts and Entities from Knowledge Base

We describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to predict entities that are relevant to the text... (read more)

PDF Abstract TACL 2017 PDF TACL 2017 Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Entity Disambiguation AIDA-CoNLL NTEE In-KB Accuracy 94.7 # 4
Entity Disambiguation TAC2010 NTEE Micro Precision 87.7 # 2

Methods used in the Paper


METHOD TYPE
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