en_core_web_lg-2.2.5
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since this release
Details: https://spacy.io/models/en#en_core_web_lg
File checksum:
994ea23a07b1c2867e1b9b21521ccb96fba582fd50e60d9d488a64a8e7230dea
English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl. Assigns word vectors, context-specific token vectors, POS tags, dependency parse and named entities.
| Feature | Description |
|---|---|
| Name | en_core_web_lg |
| Version | 2.2.5 |
| spaCy | >=2.2.2 |
| Model size | 789 MB |
| Pipeline | 聽tagger, parser, ner |
| Vectors | 684830 keys, 684831 unique vectors (300 dimensions) |
| Sources | OntoNotes 5 Common Crawl |
| License | MIT |
| Author | Explosion |
Label Scheme
| Component | Labels |
|---|---|
tagger |
聽$, '', ,, -LRB-, -RRB-, ., :, ADD, AFX, CC, CD, DT, EX, FW, HYPH, IN, JJ, JJR, JJS, LS, MD, NFP, NN, NNP, NNPS, NNS, PDT, POS, PRP, PRP$, RB, RBR, RBS, RP, SYM, TO, UH, VB, VBD, VBG, VBN, VBP, VBZ, WDT, WP, WP$, WRB, XX, _SP, ```` |
parser |
聽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 |
聽CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART |
Accuracy
| Type | Score |
|---|---|
LAS |
聽90.17 |
UAS |
聽92.01 |
TOKEN_ACC |
聽99.76 |
TAGS_ACC |
聽97.22 |
ENTS_F |
聽86.55 |
ENTS_P |
聽86.74 |
ENTS_R |
聽86.36 |
Installation
pip install spacy
python -m spacy download en_core_web_lg