Using a Partially Annotated Corpus to Build a Dependency Parser for Japanese

Abstract. We explore the use of a partially annotated corpus to build a dependency parser for Japanese. We examine two types of partially annotated corpora. It is found that a parser trained with a corpus that does not have any grammatical tags for words can demonstrate an accuracy of 87.38%, which is comparable to the current state-of-the-art accuracy on the Kyoto University Corpus. In contrast, a parser trained with a corpus that has only dependency annotations for each two adjacent bunsetsus (chunks) shows moderate performance. Nonetheless, it is notable that features based on character n-grams are found very useful for a dependency parser for Japanese.

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Manabu Sassano
• Keywords: Current State-of-the-art Accuracy, Dependency Parser, IJCNLP 2005, Kyoto University Corpus, Natural Language Processing