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arXiv:1601.01343cs.CL

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

Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji

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Abstract

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 embedding method specifically designed for NED. The proposed method jointly maps words and entities into the same continuous vector space. We extend the skip-gram model by using two models. The KB graph model learns the relatedness of entities using the link structure of the KB, whereas the anchor context model aims to align vectors such that similar words and entities occur close to one another in the vector space by leveraging KB anchors and their context words. By combining contexts based on the proposed embedding with standard NED features, we achieved state-of-the-art accuracy of 93.1% on the standard CoNLL dataset and 85.2% on the TAC 2010 dataset.

arXiv comments
Accepted at CoNLL 2016
Journal reference
DOI
Subjects
cs.CLComputation and Language

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Linked by 1 identifiable commenter in 2 comments across 2 threads, from Aug 2018 to Dec 2018.

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Discussed in comments2 threads

  1. Wikipedia2Vec: Optimized Implementation for Learning Embeddings from Wikipedia 1 comment

    • My past paper describes an entity linking method based on Wikipedia2Vec: https://arxiv.org/abs/1601.01343 You need to extract entity names using an NER software (e.g., SpaCy, Stanford NER), and resolve the names to knowledge base entities using the entity linking method.

      ikuyamadaView on HNParent context

  2. Show HN: Wikipedia2Vec – A tool for learning embeddings of words and entities 1 comment

    • Thanks :) 1) I think learning entity embeddings using the Doc2Vec (paragraph vector) model is an interesting idea, but we did not test it. 2) This tool was initially developed to address the entity linking task. Mapping words and entities into a same vector space enables to…

      ikuyamadaView on HNParent context

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