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en_core_web_trf_esco_ner
masciotta02/en_core_web_trf_esco_ner
en_core_web_trf_esco_ner is a token classification model from masciotta02. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
English transformer pipeline based on encorewebtrf plus an entity recognizer based on the ESCO taxonomy. (Transformer(name='roberta-base', pieceencoder='byte-bpe', stride=104, type='roberta', width=768, window=144, vo…
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Sep 12, 2024
- Updated
- Sep 12, 2024
- SHA
- 6ad5c41d
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Model card
From the Hugging Face model README
English transformer pipeline based on en_core_web_trf plus an entity recognizer based on the ESCO taxonomy. (Transformer(name='roberta-base', piece_encoder='byte-bpe', stride=104, type='roberta', width=768, window=144, vocab_size=50265)). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.
| Feature | Description |
|---|---|
| Name | en_core_web_trf_esco_ner |
| Version | 3.7.3 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | transformer, tagger, parser, attribute_ruler, lemmatizer, ner, entity_ruler |
| Components | transformer, tagger, parser, attribute_ruler, lemmatizer, ner, entity_ruler |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | OntoNotes 5 (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br>ClearNLP Constituent-to-Dependency Conversion (Emory University)<br>WordNet 3.0 (Princeton University)<br>roberta-base (Yinhan Liu and Myle Ott and Naman Goyal and Jingfei Du and Mandar Joshi and Danqi Chen and Omer Levy and Mike Lewis and Luke Zettlemoyer and Veselin Stoyanov) |
| License | MIT |
| Author | [email protected] |
Label Scheme
<details> <summary>View label scheme (113 labels for 4 components)</summary>| Component | Labels |
|---|---|
tagger | $, '', ,, -LRB-, -RRB-, ., :, ADD, AFX, CC, CD, DT, EX, FW, HYPH, IN, JJ, JJR, JJS, LS, MD, NFP, NN, NNP, NNPS, NNS, PDT, POS, PRP, PRP$, RB, RBR, RBS, RP, SYM, TO, UH, VB, VBD, VBG, VBN, VBP, VBZ, WDT, WP, WP$, WRB, XX, ```` |
parser | ROOT, acl, acomp, advcl, advmod, agent, amod, appos, attr, aux, auxpass, case, cc, ccomp, compound, conj, csubj, csubjpass, dative, dep, det, dobj, expl, intj, mark, meta, neg, nmod, npadvmod, nsubj, nsubjpass, nummod, oprd, parataxis, pcomp, pobj, poss, preconj, predet, prep, prt, punct, quantmod, relcl, xcomp |
ner | CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART |
entity_ruler | ESCO |
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC | 99.86 |
TOKEN_P | 99.57 |
TOKEN_R | 99.58 |
TOKEN_F | 99.57 |
TAG_ACC | 98.13 |
SENTS_P | 94.89 |
SENTS_R | 85.79 |
SENTS_F | 90.11 |
DEP_UAS | 95.26 |
DEP_LAS | 93.91 |
ENTS_P | 90.08 |
ENTS_R | 90.30 |
ENTS_F | 90.19 |
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Sep 12, 2024
- Updated
- Sep 12, 2024