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Design and Structure of The Juman++ Morphological Analyzer Toolkit

Arseny Tolmachev, Daisuke Kawahara, Sadao Kurohashi

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Arseny Tolmachev
Fujitsu Laboratories, Ltd.
Daisuke Kawahara
Kyoto University, Graduate School of Informatics
Sadao Kurohashi
Kyoto University, Graduate School of Informatics

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Keywords:Word Segmentation,Morphological Analysis,Software Optimization

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2020 Volume 27Issue 1Pages 89-132

DOIhttps://doi.org/10.5715/jnlp.27.89

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Published: March 15, 2020Received: October 29, 2019Released on J-STAGE: June 15, 2020Accepted: December 25, 2019Advance online publication: -Revised: -

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Article overview

Abstract

An NLP tool is practical when it is fast in addition to having high accuracy. We describe the architecture and the used methods to achieve 250× analysis speed improvement on the Juman++ morphological analyzer together with slight accuracy improvements. This information should be useful for implementors of high-performance NLP and machine-learning based software.

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