GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
CommonGen-Eval is designed to evaluate large language models using the CommonGen-Lite dataset, focusing on generating diverse phrases and sentences.
Good fit when
- Use CommonGen-Eval when you need to assess how well an LLM can generate a diverse set of common-sense facts or statements based on given concepts.
- Select it specifically for testing text-generation capabilities aligned with everyday language understanding and generation.
Avoid when
- Avoid using CommonGen-Eval if your evaluation priorities align more closely with task-specific benchmarks outside of general-language diversification.
- Do not use this tool if your project requires an evaluation framework that focuses heavily on the ability to answer specific factual questions or handle domain-specific language.
- Requirements:
- Install Python dependencies using `pip install -r requirements.txt`; Download necessary Spacy models with `python -m spacy download en_core_web_lg`
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (901d since push)
- As of Sep 8, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 8, 2026
- Security (OSV)
- 94 low (94 low)
- As of Jul 15, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install CommonGen-EvalSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This tool evaluates large language models using the CommonGen-Lite dataset.
Capability facts
- Languages
- python
Source: github.language · Sep 8, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 8, 2026)
python -m spacy download en_core_web_lgSource link
Tags
README
Installation
For agents
This page has a .md twin and JSON over the API.