# liuhuanyong/TextGrapher

Text Content Grapher based on keyinfo extraction by NLP method。输入一篇文档，将文档进行关键信息提取，进行结构化，并最终组织成图谱组织形式，形成对文章语义信息的图谱化展示。

Repository: https://github.com/liuhuanyong/TextGrapher
Canonical: https://ross.abutalabs.com/products/textgrapher
Language: Python
License Family: other
Last push: 2021-10-20T03:16:44+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2961, "days_push": 1778, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1468, forks 361 (observed 2026-08-28T04:04:48.932570+00:00)

## What it is
A Python library that extracts key information (high-frequency words, keywords, named entities, subject-verb-object phrases) from a document and organizes it into a graph structure. It renders the semantic representation of the text as an interactive knowledge graph in an HTML file.

## Use cases
- convert a document into a knowledge graph
- extract keywords and entities from Chinese text
- visualize the semantic structure of an article
- summarize a document as a graph
- mine events from news text

## When to choose
- you need a quick graph-based semantic overview of a Chinese-language document
- you want keyword, NER, and SVO extraction combined into one visualization

## When to avoid
- you need production-grade NLP accuracy or active maintenance
- you need multilingual support beyond Chinese
- you require a maintained license or long-term support

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, data-visualization, parser
- domain: data-visualization, artificial-intelligence
- platform: python
- tags: knowledge-graph, text-summarization, keyphrase-extraction, named-entity-recognition, chinese-nlp, graph-visualization, natural-language-processing

## Member repositories
- liuhuanyong/TextGrapher (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:48.932570+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 2026-08-30T04:34:57.033770+00:00, confidence not recorded.
  - readme: https://github.com/liuhuanyong/TextGrapher (fetched 2026-08-28T04:04:48.932570+00:00, sha 8a70f26c00c7)
- Data as of 2026-08-30T08:39:29.467469+00:00.