Demos
Legal NLP 1.13 comes with a lot of new capabilities added to the 926+ models and 125+ Language Models already available in previous versions of the library. Let’s take a look at each of them!
New Subpoenas NER
Identify the required documents to present in the subpoena with DOCUMENT_TYPE (as records, emails, memos, written communication, sms, etc) and their DOCUMENT_TOPIC (about what the documents should be about), the people involved in the notification — PERSON (, DATES, COURTS contact information including notification date, etc.
Improvements in NDA models
Three out of our more than 20 NDA models were improved. More specifically:
- Detection of Confidencial Information types (written information, oral, orally, via facsimile, etc)
- Detection of purposes of the NDA (“entering”, “exploring”, “considering”… “acquisition”, “merge”, “business relationship”…)
- Detection of Alias (“Receiver”, “Submitter”, …)
- Detection of Parties with more unusual names
- Classification of the paragraphs of an NDA into 15 categories (“Names of the parties”, “Preamble”, “Definition of Confidential Information”, “Requirement of Confidential Information”, “Disclosures”, “Non-compete and Non-solicitation clauses”, etc).
Legal Greek NLP
We have released several Legal Greek models, including classification and NER.
Legal Turkish Classification
We also released Turkish Legal NLP classification based on Constitutional Court Decisions.
Fancy trying?
We’ve got 30-days free licenses for you with technical support from our legal team of technical and SME. This trial includes complete access to more than 926 models, including Classification, NER, Relation Extraction, Similarity Search, Summarization, Sentiment Analysis, Question Answering, etc. and 120+ legal language models.
Want to try NLP for contracts? Just go to https://www.johnsnowlabs.com/install/ and follow the instructions!
How to run
NLP for Legal is very easy to run on both clusters and driver-only environments using johnsnowlabs library:
!pip install johnsnowlabs
nlp.install(force_browser=True) nlp.start()
