利用大模型LLM对中文文本、图片以及pdf中的非结构化文本内容进行分析，并提取主-谓-宾（SPO）三元组的知识形式，以及将这些关系可视化为知识图谱。The large LLM model is used to analyze the unstructured text content in Chinese text, picture and pdf, extract the knowledge form of subject-predicate-object (SPO) triad, and visualize these relations as knowledge graph.
active 2025-04-16 → 2026-03-08 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 327 days from 2025-04-16 to 2026-03-08. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 14 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| jiangnanboy | 1 | 1 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 14 stars here means stars gained during the window, not the repo's star count.