Skip to main content

No project description provided

Project description

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

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

Feature Description
Name en_core_web_md
Version 3.7.1
spaCy >=3.7.2,<3.8.0
Default Pipeline tok2vec, tagger, parser, attribute_ruler, lemmatizer, ner
Components tok2vec, tagger, parser, senter, attribute_ruler, lemmatizer, ner
Vectors 514157 keys, 20000 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)
Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl) (Explosion)
License MIT
Author Explosion

Label Scheme

View label scheme (113 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, _SP, ````
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 99.86
TOKEN_P 99.57
TOKEN_R 99.58
TOKEN_F 99.57
TAG_ACC 97.33
SENTS_P 92.21
SENTS_R 89.37
SENTS_F 90.77
DEP_UAS 92.05
DEP_LAS 90.23
ENTS_P 84.94
ENTS_R 85.49
ENTS_F 85.22

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spacy_md_pipeline-3.7.1.tar.gz (42.8 MB view details)

Uploaded Source

Built Distribution

spacy_md_pipeline-3.7.1-py3-none-any.whl (42.8 MB view details)

Uploaded Python 3

File details

Details for the file spacy_md_pipeline-3.7.1.tar.gz.

File metadata

  • Download URL: spacy_md_pipeline-3.7.1.tar.gz
  • Upload date:
  • Size: 42.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.11.3

File hashes

Hashes for spacy_md_pipeline-3.7.1.tar.gz
Algorithm Hash digest
SHA256 118f875909f6b5e8e69d872363d44a020995fcbd6c4c74815e48d9de2bfd8fab
MD5 8335ba35fbe532976cd180bffc1b33dd
BLAKE2b-256 ed64ea8d96c0846a56d5fae7edb011f7aa821fd4a3e27ee03bc3da500e2e76a1

See more details on using hashes here.

File details

Details for the file spacy_md_pipeline-3.7.1-py3-none-any.whl.

File metadata

File hashes

Hashes for spacy_md_pipeline-3.7.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c2b55dcb0592ae8c93aa208d6e27d67c3b3a83457ed33056079e0630c175eda5
MD5 f8689fd3d7a28ea6519d19bc6627b018
BLAKE2b-256 9abe3874b688912f86f299be63c34993c9ffdbd9012b36d63ad98048a78e6acb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page