Hideaki Takeda

LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention

2020

Entity representations are useful in natural language tasks involving entities. In this paper, we propose new pretrained contextualized representations of words and entities based on the bidirectional transformer The proposed model treats words and entities …

Learning Distributed Representations of Texts and Entities from Knowledge Base

2017 · Transactions of the Association for Computational Linguistics

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 …

Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation

2016

Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity mentions in a document to their correct references in a knowledge base (KB) (e.g., Wikipedia). In this paper, we propose a novel …