Blackstone — Legal NER & Text Categorizer

Blackstone — Legal NER & Text Categorizer

Blackstone is an Apache-licensed spaCy NLP pipeline trained on the Incorporated Council of Law Reporting for England and Wales (ICLR&D) corpus. It provides named entity recognition purpose-built for legal text — identifying cases, legislation, provisions, instruments, neutral citations, and court references. It also ships a text categorizer for classifying sentence types in legal documents (issue, ratio, legal test, etc.).

Key Features

• Custom NER for legal entities: CASENAME, CITATION, LEGISLATION, PROVISION, INSTRUMENT, COURT
• Sentence-level text categorizer trained on case law
• Span-level co-reference resolution for legal citations
• Abbreviation detection for statute shorthand
• Built on spaCy 3 — integrates with any spaCy pipeline

Quick Start

pip install blackstone
python -m blackstone.pipeline.download

import spacy
from blackstone.pipeline.abbreviations import AbbreviationDetector

nlp = spacy.load("en_blackstone_proto")
text = "The court in Donoghue v Stevenson [1932] AC 562 held that a duty of care existed."
doc = nlp(text)
for ent in doc.ents:
    print(ent.text, ent.label_)
# Donoghue v Stevenson [1932] AC 562  CASENAME

npx ai-supply add blackstone-legal-nlp

Curated mirror of the open-source Blackstone (Apache-2.0). Get it from the source.