Statements (53)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Model
|
| gptkbp:application |
contract analysis
regulatory compliance analysis case law retrieval legal information extraction legal question answering |
| gptkbp:architecture |
transformer-based
|
| gptkbp:available_on |
gptkb:Hugging_Face_Model_Hub
|
| gptkbp:based_on |
BERT architecture
|
| gptkbp:can_be_used_for |
litigation support
risk assessment in legal matters legal compliance checks automated legal advice discovery process in legal cases document summarization in legal field entity recognition in legal texts legal drafting assistance legal knowledge management sentiment analysis in legal texts topic modeling in legal documents |
| gptkbp:community |
open-source
|
| gptkbp:contributes_to |
legal AI research
|
| gptkbp:developed_by |
gptkb:Hugging_Face
|
| gptkbp:enhances |
legal analytics
|
| gptkbp:evaluates |
gptkb:historical_memory
F1 score accuracy precision |
| gptkbp:facilitates |
legal document review
|
| https://www.w3.org/2000/01/rdf-schema#label |
Legal BERT
|
| gptkbp:improves |
legal research efficiency
legal NLP tasks |
| gptkbp:inspired_by |
gptkb:BERT
|
| gptkbp:is_adopted_by |
government agencies
non-profit organizations academic institutions law firms legal tech companies |
| gptkbp:is_trained_in |
gptkb:legal_documents
|
| gptkbp:language |
English
|
| gptkbp:performance |
state-of-the-art in legal NLP
|
| gptkbp:provides |
contextual embeddings
|
| gptkbp:provides_information_on |
Case Law dataset
Contracts dataset Legal Text dataset |
| gptkbp:released_in |
gptkb:2020
|
| gptkbp:supports |
gptkb:Tensor_Flow
gptkb:Py_Torch multi-task learning |
| gptkbp:tuning |
legal domain tasks
|
| gptkbp:used_for |
legal text classification
|
| gptkbp:bfsParent |
gptkb:Super_GLUE_benchmark
|
| gptkbp:bfsLayer |
5
|