Legal-NLP-EkStep/legal_NER
OpenNyAI is a mission aimed at developing open source software and datasets to catalyze the creation of AI-powered solutions to improve access to justice in India. Legal NER is one the AI component developed under this mission
This tool helps legal professionals automatically identify and extract key pieces of information from Indian court judgments. It takes raw judgment text as input and outputs a structured list of named entities like court names, parties involved (petitioner, respondent), judges, lawyers, dates, statutes, provisions, and precedents. This is designed for lawyers, legal researchers, paralegals, or anyone who needs to quickly parse Indian legal documents for critical details.
No commits in the last 6 months.
Use this if you need to rapidly extract specific facts and entities from large volumes of Indian court judgments, saving significant manual review time.
Not ideal if you are working with legal documents from other jurisdictions or if your task requires extracting entities not specifically covered by the predefined list.
Stars
92
Forks
37
Language
Python
License
Apache-2.0
Category
Last pushed
May 15, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Legal-NLP-EkStep/legal_NER"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
hellohaptik/chatbot_ner
chatbot_ner: Named Entity Recognition for chatbots.
openeventdata/mordecai
Full text geoparsing as a Python library
Rostlab/nalaf
NLP framework in python for entity recognition and relationship extraction
mpuig/spacy-lookup
Named Entity Recognition based on dictionaries
NorskRegnesentral/skweak
skweak: A software toolkit for weak supervision applied to NLP tasks