nestauk/en_skillner

A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.

Feature	Description
Name	en_skillner
Version	3.7.1
spaCy	>=3.7.4,<3.8.0
Default Pipeline	tok2vec, tagger, parser, attribute_ruler, lemmatizer, ner
Components	tok2vec, tagger, parser, senter, attribute_ruler, lemmatizer, ner
Vectors	514157 keys, 514157 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	nestauk

Label Scheme

View label scheme (3 labels for 1 components)

Component	Labels
ner	SKILL, EXPERIENCE, BENEFIT

Accuracy

Type	Score
ENTS_P	59.19
ENTS_R	57.58
ENTS_F	58.38
SKILL_P	72.19
SKILL_R	72.62
SKILL_F	72.40
EXPERIENCE_P	52.14
EXPERIENCE_R	41.48
EXPERIENCE_F	46.20
BENEFIT_P	75.61
BENEFIT_R	46.27
BENEFIT_F	57.41