jieba-php
Segment Chinese text in PHP applications with jieba-php, a library for Chinese word tokenization.
About jieba-php
jieba-php is an open-source PHP library for segmenting Chinese text into words. It provides precise, full, and search-engine modes through cut and cutForSearch methods that accept UTF-8 strings and return iterable arrays.
It supports Traditional Chinese via big dictionary mode, custom user dictionaries, CJK text handling, TF-IDF integration, and part-of-speech tagging. Full mode scans all possible words but does not resolve ambiguity and needs a sufficient dictionary, and the project notes that LLM models may give better segmentation results.
Key features
- Precise, full, and search-engine Chinese segmentation modes
- Traditional Chinese segmentation using big dictionary mode
- Custom user dictionary loading for domain-specific terms
- CJK text handling for Chinese, Japanese, and Korean
- TF-IDF integration and part-of-speech tagging
- cut and cutForSearch methods returning iterable arrays
Best for: PHP developers who need to add Chinese word segmentation to applications.
Good for
- Offers three segmentation modes for text analysis and search
- Supports custom dictionaries and custom part-of-speech tags
- Installable via Composer with manual install option
Watch out for
- Full mode does not resolve ambiguity
- Full mode requires a sufficient dictionary
- Project notes LLMs may produce better segmentation results
jieba-php at a glance
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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jieba-php FAQ
How do I install jieba-php?
Run composer require fukuball/jieba-php and load it through Composer autoload, or place the files manually and include them with require_once.
How do I handle Traditional Chinese?
Switch the dictionary to big mode.
How do I add custom terms?
Use Jieba::loadUserDict with the absolute path to a dictionary file where each line contains a word, frequency, and part of speech separated by spaces.
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