liuhuanyong/ComplexEventExtraction
A concept and obvious expression pattern collection of Chinese compound event extraction which then be evolved into ComplexEventGraph，本项目提出了中文复合事件的概念与显式模式，包括条件事件、因果事件、顺承事件、反转事件等事件抽取，并形成事理图谱。 observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2893
- days_rel: n/a
- days_push: 2818
- n_releases_24m: 0
Adoption not part of the score
1227 stars · 282 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python library for Chinese compound event extraction that identifies conditional, causal, sequential, and adversative events using explicit conjunction patterns, building event graphs (event logic graphs). It collects Chinese complex-sentence connective patterns and applies them to large-scale news corpora to extract event pairs.
Use cases
- extract causal events from Chinese text
- build an event logic graph from news corpora
- detect conditional and adversative event relations in Chinese sentences
- mine sequential event pairs for intent prediction
- research Chinese complex sentence connective patterns
When to choose
- you need rule-based Chinese event relation extraction without training data
- you want to construct event graphs from large Chinese text corpora
- you need a curated collection of Chinese complex-sentence conjunction patterns
When to avoid
- you need multilingual event extraction
- you require actively maintained software with a license
- you need neural or state-of-the-art event extraction models
Facets
library · maturity maintenance
nlp parser machine-learning artificial-intelligence python cross-platform event-extraction event-graph chinese-nlp causality information-extraction complex-events natural-language-processing algorithms
1 source
- readme: https://github.com/liuhuanyong/ComplexEventExtraction · fetched 2026-08-28 · 7d10d2b3ae7e
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| liuhuanyong/ComplexEventExtraction | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="liuhuanyong/ComplexEventExtraction")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem