Summary
English: strongest average flat F1 isFlair NER ENat0.720; fastest average p50 isspaCy EntityRecognizer XXat1.54 ms.Polish: strongest average flat F1 isStanza NER PLat0.684; fastest average p50 isspaCy EntityRecognizer XXat6.31 ms.- Caveat: 21 long documents were truncated to 384 tokens (input length range 1217-2645).
Run Metadata
| Field | Value |
|---|---|
| Benchmark | NER OSS Reference Benchmark |
| Generated at | 2026-06-05T14:33:28.697085+00:00 |
| Processor | Apple M1 Pro |
| Python | 3.12.10 |
English Quality And Speed
| Dataset | Best quality | F1 | p50 ms | Fastest | p50 ms | Fastest F1 |
|---|---|---|---|---|---|---|
| CoNLL-2003 EN Test | Flair NER EN | 0.912 | 42.44 | spaCy EntityRecognizer XX | 1.38 | 0.604 |
| WikiNER EN Test | spaCy EntityRecognizer XX | 0.811 | 2.05 | spaCy EntityRecognizer XX | 2.05 | 0.811 |
| WikiANN EN Test | Flair NER EN | 0.491 | 34.81 | spaCy EntityRecognizer XX | 1.21 | 0.447 |
Polish Quality And Speed
| Dataset | Best quality | F1 | p50 ms | Fastest | p50 ms | Fastest F1 |
|---|---|---|---|---|---|---|
| PolEval-2018 PL Test | Stanza NER PL | 0.732 | 581.55 | spaCy EntityRecognizer XX | 16.01 | 0.372 |
| WikiNER PL Test | spaCy EntityRecognizer XX | 0.857 | 1.68 | spaCy EntityRecognizer XX | 1.68 | 0.857 |
| WikiANN PL Test | Stanza NER PL | 0.656 | 43.89 | spaCy EntityRecognizer XX | 1.25 | 0.610 |
English Model x Dataset Heatmaps
Higher F1 is strongerHigher p50 is slower
Flat F1
| Provider | CoNLL-2003 EN Test | WikiNER EN Test | WikiANN EN Test |
|---|---|---|---|
| Flair NER EN | 0.912 | 0.757 | 0.491 |
| Flair NER EN OntoNotes | 0.546 | 0.541 | 0.366 |
| GLiNER Multi | 0.357 | 0.351 | 0.269 |
| Stanza NER EN | 0.495 | 0.537 | 0.379 |
| spaCy EntityRecognizer EN | 0.438 | 0.410 | 0.311 |
| spaCy EntityRecognizer XX | 0.604 | 0.811 | 0.447 |
p50 Latency
| Provider | CoNLL-2003 EN Test | WikiNER EN Test | WikiANN EN Test |
|---|---|---|---|
| Flair NER EN | 42.44 | 108.38 | 34.81 |
| Flair NER EN OntoNotes | 42.74 | 107.97 | 35.19 |
| GLiNER Multi | 59.96 | 68.63 | 59.96 |
| Stanza NER EN | 46.86 | 117.37 | 39.84 |
| spaCy EntityRecognizer EN | 3.38 | 5.30 | 2.87 |
| spaCy EntityRecognizer XX | 1.38 | 2.05 | 1.21 |
Polish Model x Dataset Heatmaps
Higher F1 is strongerHigher p50 is slower
Flat F1
| Provider | PolEval-2018 PL Test | WikiNER PL Test | WikiANN PL Test |
|---|---|---|---|
| GLiNER Multi | 0.166 | 0.524 | 0.426 |
| Stanza NER PL | 0.732 | 0.666 | 0.656 |
| spaCy EntityRecognizer PL | 0.632 | 0.527 | 0.463 |
| spaCy EntityRecognizer XX | 0.372 | 0.857 | 0.610 |
p50 Latency
| Provider | PolEval-2018 PL Test | WikiNER PL Test | WikiANN PL Test |
|---|---|---|---|
| GLiNER Multi | 307.28 | 68.18 | 60.58 |
| Stanza NER PL | 581.55 | 104.34 | 43.89 |
| spaCy EntityRecognizer PL | 61.40 | 6.38 | 4.66 |
| spaCy EntityRecognizer XX | 16.01 | 1.68 | 1.25 |
English Leaderboard
| Provider | Official benchmark | Official F1 | CoNLL-2003 EN Test | WikiNER EN Test | WikiANN EN Test |
|---|---|---|---|---|---|
| spaCy EntityRecognizer EN | OntoNotes 5 | 0.843 | 0.438 | 0.410 | 0.311 |
| spaCy EntityRecognizer XX | WikiNER | 0.831 | 0.604 | 0.811 | 0.447 |
| Flair NER EN | CoNLL-03 | 0.929 | 0.912 | 0.757 | 0.491 |
| Flair NER EN OntoNotes | OntoNotes | 0.893 | 0.546 | 0.541 | 0.366 |
| Stanza NER EN | OntoNotes | 0.888 | 0.495 | 0.537 | 0.379 |
| GLiNER Multi | n/a | n/a | 0.357 | 0.351 | 0.269 |
Polish Leaderboard
| Provider | Official benchmark | Official F1 | PolEval-2018 PL Test | WikiNER PL Test | WikiANN PL Test |
|---|---|---|---|---|---|
| spaCy EntityRecognizer PL | NKJP / package validation | 0.804 | 0.632 | 0.527 | 0.463 |
| spaCy EntityRecognizer XX | WikiNER | 0.831 | 0.372 | 0.857 | 0.610 |
| Stanza NER PL | NKJP | 0.887 | 0.732 | 0.666 | 0.656 |
| GLiNER Multi | n/a | n/a | 0.166 | 0.524 | 0.426 |