Multi-prototype Chinese Character Embedding
Yanan Lu, Yue Zhang, Donghong Ji · 2016
Chinese sentences are written as sequences of characters, which are elementary units of syntax and semantics.Characters are highly polysemous in forming words.We present a position-sensitive skip-gram model to learn multi-prototype Chinese character embeddings, and explore the usefulness of such character embeddings to Chinese NLP tasks.Evaluation on character similarity shows that multi-prototype embeddings are significantly better than a single-prototype baseline.In addition, used as features in the Chinese NER task, the embeddings result in a 1.74% F-score improvement over a state-of-the-art baseline.