Modeling Named Entity Embedding Distribution into Hypersphere

no code implementations • 3 Sep 2019 • Zhuosheng Zhang, Bingjie Tang, Zuchao Li, Hai Zhao

This work models named entity distribution from a way of visualizing topological structure of embedding space, so that we make an assumption that most, if not all, named entities (NEs) for a language tend to aggregate together to be accommodated by a specific hypersphere in embedding space.

named-entity-recognition Named Entity Recognition +1

Open Named Entity Modeling from Embedding Distribution

no code implementations • 31 Aug 2019 • Ying Luo, Hai Zhao, Zhuosheng Zhang, Bingjie Tang

For monolingual cases, the proposed named entity model gives an open description of diverse named entity types and different languages.

named-entity-recognition Named Entity Recognition +2

SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings

no code implementations • SEMEVAL 2018 • Zhuosheng Zhang, Jiangtong Li, Hai Zhao, Bingjie Tang

This paper describes a hypernym discovery system for our participation in the SemEval-2018 Task 9, which aims to discover the best (set of) candidate hypernyms for input concepts or entities, given the search space of a pre-defined vocabulary.

Hypernym Discovery