# crownpku/Rasa_NLU_Chi

Turn Chinese natural language into structured data 中文自然语言理解

Repository: https://github.com/crownpku/Rasa_NLU_Chi
Canonical: https://ross.abutalabs.com/products/rasa_nlu_chi
Language: Python
License: Apache-2.0
License Family: permissive
Topics: natural-language, chinese, chatbot
Last push: 2024-07-30T21:17:04+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3360, "days_push": 764, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1531, forks 417 (observed 2026-08-28T04:04:59.402239+00:00)

## What it is
A Chinese-language fork of Rasa NLU that turns Chinese natural language into structured intent and entity data using MITIE, Jieba tokenization, and sklearn pipelines. It provides training and serving of Chinese NLU models for chatbot and conversational applications.

## Use cases
- build a Chinese chatbot that understands intents and entities
- extract entities from Chinese text
- classify user intents in Chinese
- tokenize Chinese text with custom dictionaries for NLU
- train a Chinese NLU model from labeled examples

## When to choose
- you need intent classification and entity extraction specifically for Chinese
- you want a self-hosted Rasa NLU pipeline with Jieba and MITIE support

## When to avoid
- you need modern actively maintained NLU - use Rasa 3.x or newer alternatives instead
- your project is not Chinese-language NLU
- you want a managed cloud NLU service

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, machine-learning, chatbot
- domain: chatbots, machine-learning
- platform: python, cross-platform
- tags: chinese-nlu, intent-classification, named-entity-recognition, jieba, mitie, rasa-fork, natural-language-processing

## Member repositories
- crownpku/Rasa_NLU_Chi (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:59.402239+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:31:22.252710+00:00, confidence not recorded.
  - readme: https://github.com/crownpku/Rasa_NLU_Chi (fetched 2026-08-28T04:04:59.402239+00:00, sha 99c019fb7278)
- Data as of 2026-08-30T08:39:29.467469+00:00.