Makoto Yamazaki


2022

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CHJ-WLSP: Annotation of ‘Word List by Semantic Principles’ Labels for the Corpus of Historical Japanese
Masayuki Asahara | Nao Ikegami | Tai Suzuki | Taro Ichimura | Asuko Kondo | Sachi Kato | Makoto Yamazaki
Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages

This article presents a word-sense annotation for the Corpus of Historical Japanese: a mashed-up Japanese lexicon based on the ‘Word List by Semantic Principles’ (WLSP). The WLSP is a large-scale Japanese thesaurus that includes 98,241 entries with syntactic and hierarchical semantic categories. The historical WLSP is also compiled for the words in ancient Japanese. We utilized a morpheme-word sense alignment table to extract all possible word sense candidates for each word appearing in the target corpus. Then, we manually disambiguated the word senses for 647,751 words in the texts from the 10th century to 1910.

2018

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Annotation of ‘Word List by Semantic Principles’ Labels for the Balanced Corpus of Contemporary Written Japanese
Sachi Kato | Masayuki Asahara | Makoto Yamazaki
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation

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Annotation and Quantitative Analysis of Speaker Information in Novel Conversation Sentences in Japanese
Makoto Yamazaki | Yumi Miyazaki | Wakako Kashino
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2010

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Design, Compilation, and Preliminary Analyses of Balanced Corpus of Contemporary Written Japanese
Kikuo Maekawa | Makoto Yamazaki | Takehiko Maruyama | Masaya Yamaguchi | Hideki Ogura | Wakako Kashino | Toshinobu Ogiso | Hanae Koiso | Yasuharu Den
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Compilation of a 100 million words balanced corpus called the Balanced Corpus of Contemporary Written Japanese (or BCCWJ) is underway at the National Institute for Japanese Language and Linguistics. The corpus covers a wide range of text genres including books, magazines, newspapers, governmental white papers, textbooks, minutes of the National Diet, internet text (bulletin board and blogs) and so forth, and when possible, samples are drawn from the rigidly defined statistical populations by means of random sampling. All texts are dually POS-analyzed based upon two different, but mutually related, definitions of ‘word.’ Currently, more than 90 million words have been sampled and XML annotated with respect to text-structure and lexical and character information. A preliminary linear discriminant analysis of text genres using the data of POS frequencies and sentence length revealed it was possible to classify the text genres with a correct identification rate of 88% as far as the samples of books, newspapers, whitepapers, and internet bulletin boards are concerned. When the samples of blogs were included in this data set, however, the identification rate went down to 68%, suggesting the considerable variance of the blog texts in terms of the textual register and style.