A spaCy Package for Romanian Legal Document Processing

rolegal: a spaCy Package for Noisy Romanian Legal Document Processing

This is a spaCy language model for Romanian legal domain trained with floret 4-gram to 5-gram embeddings and LEGAL entity recognition. Useful for processing OCR-resulted noisy legal documents.

Example
import spacy
nlp = spacy.load("ro_legal_fl")

doc = nlp("Titlul III din LEGEA nr. 255 din 19 iulie 2013, publicată în MONITORUL OFICIAL")
# legal entity identification
for entity in doc.ents:
    print('entity: ', entity, '; entity type: ', entity.label_)

# floret n-gram embeddings robust to typos
print(nlp('achizit1e public@').similarity(nlp('achiziții publice')))
# 0.7393895566928835
print(nlp('achizitii publice').similarity(nlp('achiziții publice')))
# 0.8996480808279399

Author info

Sergiu Nisioi

GitHubsenisioi/rolegal

Categories pipeline training models

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