mk_core_news_lg-3.0.0

Details: https://spacy.io/models/mk#mk_core_news_lg

Checksum .tar.gz: d2c191614cc9aa7bbb0c038cb5bc8517c4dbe2f2930b404e8bcdd29bf0bbb9ba
Checksum .whl: 49f408841f8ee22bd0a9eddb2d31bd4c651f5cd30b3b13e6e6dbf7e0da3411f7

Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.

Feature	Description
Name	mk_core_news_lg
Version	3.0.0
spaCy	>=3.0.0,<3.1.0
Model size	312 MB
Default Pipeline	morphologizer, parser, ner, attribute_ruler, lemmatizer
Components	morphologizer, parser, senter, ner, attribute_ruler, lemmatizer
Vectors	274587 keys, 274587 unique vectors (300 dimensions)
Sources	Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)
License	CC BY-SA 4.0
Author	Explosion

Label Scheme

View label scheme (54 labels for 4 components)

Component	Labels
morphologizer	POS=PROPN, POS=AUX, POS=ADJ, POS=NOUN, POS=ADP, POS=PUNCT, POS=CONJ, POS=NUM, POS=VERB, POS=PRON, POS=ADV, POS=SCONJ, POS=PART, POS=SYM, POS=X, POS=INTJ
parser	ROOT, advmod, att, aux, cc, dep, det, dobj, iobj, neg, nsubj, pobj, poss, pozm, pozv, prep, punct, relcl
senter	I, S
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	100.00
ENTS_P	76.48
ENTS_R	75.83
ENTS_F	76.15
SENTS_P	78.79
SENTS_R	67.53
SENTS_F	72.73
POS_ACC	93.31
DEP_UAS	67.65
DEP_LAS	51.37

Installation

pip install spacy
python -m spacy download mk_core_news_lg