metadata
tags:
- spacy
- token-classification
language:
- mk
license: cc-by-sa-4.0
model-index:
- name: mk_core_news_lg
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.7506382979
- name: NER Recall
type: recall
value: 0.7506382979
- name: NER F Score
type: f_score
value: 0.7506382979
- task:
name: POS
type: token-classification
metrics:
- name: POS (UPOS) Accuracy
type: accuracy
value: 0.9309414621
- task:
name: UNLABELED_DEPENDENCIES
type: token-classification
metrics:
- name: Unlabeled Attachment Score (UAS)
type: f_score
value: 0.6783968719
- task:
name: LABELED_DEPENDENCIES
type: token-classification
metrics:
- name: Labeled Attachment Score (LAS)
type: f_score
value: 0.5298142717
- task:
name: SENTS
type: token-classification
metrics:
- name: Sentences F-Score
type: f_score
value: 0.6756756757
Details: https://spacy.io/models/mk#mk_core_news_lg
Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.
Feature | Description |
---|---|
Name | mk_core_news_lg |
Version | 3.7.0 |
spaCy | >=3.7.0,<3.8.0 |
Default Pipeline | morphologizer , parser , attribute_ruler , lemmatizer , ner |
Components | morphologizer , parser , senter , attribute_ruler , lemmatizer , ner |
Vectors | 274587 keys, 274587 unique vectors (300 dimensions) |
Sources | Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) spaCy lookups data (Explosion) Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia) (Explosion) |
License | CC BY-SA 4.0 |
Author | Explosion |
Label Scheme
View label scheme (54 labels for 3 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=SPACE , POS=X , POS=INTJ |
parser |
ROOT , advmod , att , aux , cc , dep , det , dobj , iobj , neg , nsubj , pobj , poss , pozm , pozv , prep , punct , relcl |
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 |
TOKEN_P |
100.00 |
TOKEN_R |
100.00 |
TOKEN_F |
100.00 |
SENTS_P |
70.42 |
SENTS_R |
64.94 |
SENTS_F |
67.57 |
DEP_UAS |
67.84 |
DEP_LAS |
52.98 |
ENTS_P |
75.06 |
ENTS_R |
75.06 |
ENTS_F |
75.06 |
POS_ACC |
93.09 |