github explosion/spacy-models en_core_web_lg-3.3.0

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Checksum .tar.gz: 432ae42b4c26fab11574b48a8d47ef543a2b48fdf0a990bf8f6a61dc454c2d48
Checksum .whl: 6ce19d37dfe5280400f80a5954d41afca10cbc742b97bfcf4b0e452b6eb24273

Details: https://spacy.io/models/en#en_core_web_lg

English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.

Feature Description
Name en_core_web_lg
Version 3.3.0
spaCy >=3.3.0.dev0,<3.4.0
Default Pipeline tok2vec, tagger, parser, attribute_ruler, lemmatizer, ner
Components tok2vec, tagger, parser, senter, attribute_ruler, lemmatizer, ner
Vectors 684830 keys, 342918 unique vectors (300 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)
ClearNLP Constituent-to-Dependency Conversion (Emory University)
WordNet 3.0 (Princeton University)
GloVe Common Crawl (Jeffrey Pennington, Richard Socher, and Christopher D. Manning)
License MIT
Author Explosion
Model size 382 MB

Label Scheme

View label scheme (112 labels for 3 components)
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

Accuracy

Type Score
TOKEN_ACC 99.93
TOKEN_P 99.57
TOKEN_R 99.58
TOKEN_F 99.57
TAG_ACC 97.38
SENTS_P 91.77
SENTS_R 88.94
SENTS_F 90.34
DEP_UAS 91.89
DEP_LAS 90.08
ENTS_P 86.02
ENTS_R 84.63
ENTS_F 85.32

Installation

pip install spacy
python -m spacy download en_core_web_lg

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