it_core_news_sm-2.1.0a0

Details: https://spacy.io/models/it#it_core_news_sm

File checksum: 6cdaace95334a98d579fdaf0d1d885df9743430c0628d9a344d9fd2559dcce9a

Italian multi-task CNN trained on the Universal Dependencies and WikiNER corpus. Assigns context-specific token vectors, POS tags, dependency parse and named entities. Supports identification of PER, LOC, ORG and MISC entities.

Feature	Description
Name	it_core_news_sm
Version	2.1.0a0
spaCy	>=2.1.0a0
Model size	27 MB
Pipeline	tagger, parser, ner
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	Universal Dependencies, Wikipedia
License	CC BY-NC-SA 3.0
Author	Explosion AI

Accuracy

Type	Score
ENTS_F	81.25
ENTS_P	81.51
ENTS_R	81.00
LAS	87.09
TAGS_ACC	96.08
TOKEN_ACC	100.00
UAS	90.73

Because the model is trained on Wikipedia, it may perform inconsistently on many genres, such as social media text. The NER accuracy refers to the "silver standard" annotations in the WikiNER corpus. Accuracy on these annotations tends to be higher than correct human annotations.

Installation

pip install spacy-nightly
spacy download it_core_news_sm