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CLUEbenchmark/CLUENER2020 resource

CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition observed · 2026-08-28

github.com/CLUEbenchmark/CLUENER2020 · homepage · Python 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: 2432
  • days_rel: n/a
  • days_push: 1381
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1521 stars · 296 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CLUENER2020 is a fine-grained Chinese named entity recognition dataset and benchmark with 10 entity categories (address, book, company, game, government, movie, name, organization, position, scene), containing ~10,748 training and 1,343 validation sentences. It also provides baseline models such as BERT, RoBERTa, and BiLSTM+CRF for sequence labeling evaluation.

Use cases

  • train a Chinese named entity recognition model
  • benchmark NER models on Chinese text
  • fine-tune BERT for Chinese sequence labeling
  • evaluate fine-grained entity extraction in Chinese
  • get labeled Chinese NER training data
  • compare Chinese NER model performance against baselines

When to choose

  • you need a well-defined, challenging Chinese NER dataset with diverse entity categories beyond person/location/organization
  • you want to benchmark Chinese NER models against published baselines and a leaderboard

When to avoid

  • you need NER data for languages other than Chinese
  • you need a permissively licensed dataset - the repo has no license specified
  • you need actively maintained tooling rather than a dataset and baselines

Facets

dataset · maturity maintenance

nlp machine-learning benchmarking machine-learning artificial-intelligence python named-entity-recognition chinese-ner sequence-labeling bert fine-grained-ner benchmark seq2seq natural-language-processing

6 sources

Member repositories

RepositoryRoleHealth v2
CLUEbenchmark/CLUENER2020main32

For agents

markdown · JSON · MCP: product_card(name="CLUEbenchmark/CLUENER2020")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem