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.
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Sassano, M. (2005). Using a Partially Annotated Corpus to Build a Dependency Parser for Japanese. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_8
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DOI: https://doi.org/10.1007/11562214_8
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