taishi-i/nagisa

What it solves

Nagisa addresses the challenge of processing Japanese text by providing a simple, easy-to-use tool for word segmentation and part-of-speech (POS) tagging. Since Japanese does not use spaces between words, this tool automatically breaks sentences into individual words and identifies their grammatical roles.

How it works

The tool is built on recurrent neural networks. It combines character- and word-level features for accurate word segmentation and utilizes tag dictionary information to improve the precision of its POS tagging. It also includes built-in support for filtering, extracting specific word types, handling custom user dictionaries, and managing Japanese stopwords.

Who it’s for

It is designed for developers and researchers working with Japanese language data who need a straightforward, Python-based library for natural language processing tasks like tokenization, POS tagging, or custom sequence labeling.

Highlights

• Simple Python API for quick integration.
• Built-in support for filtering and extracting words based on POS tags.
• Easy customization via user-defined dictionaries for specific terminology.
• Includes a pre-defined list of Japanese stopwords.
• Supports custom model training for specialized sequence labeling tasks.