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Open Source AI Driven Solution to Manage Legal Research.

Vern R. Walker and Stephen R. Strong, "Toward Implementation Science: A Case Study Using LA-MPS to Research Argument Elements at Scale," in Proceedings of the Sixth Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL 2023), June 23, 2023, Braga, Portugal.

Fork on GitHub Watch on YouTube

Legal Marker

Mark up your personal cases with detailed notes. Classify each sentence to build strong arguments.

Legal Pad

Collaborate with team members while taking notes on multiple cases. (Not part of Azure Demo.)

Legal Search

Search your personal cases using powerful 'google-like' tools and semantic information.

LAMPS Architecture

Three independent solutions connected by a common portable web server, connected to open-source elastic search database

Client / Server Architecture

Modern Web-App architecture

Dockerized for Desktop or Cloud Deployment

Source code includes Docker definition files so you are in control of how / where the solution is deployed.

Download the Paper

LA-Marker

is a web application with a user interface for viewing and annotating individual legal documents.

It is written using the open-source Angular web framework from Google.

Label Sentences for Machine Learning

Version and Save Cases in LS-Json Format

Import Cases from Raw Text or Html

LA-Pad

is a web application connecting LA-Marker and LA-Search with live collaboration.

It is a user interface for grouping and annotating selections of sentences and paragraphs sent to it from LA-Marker or from LA-Search (see below). (Note: LA-Pad is omitted from the Azure demonstration deployment because it would require login and authentication functionality.)

Extract sentences from many different legal documents

Save and reuse your notes

Integrated to LA-Marker and LA-Search

LA-Search

is a web application with a user interface for searching a large set of documents that have been semantically enriched.

It is currently configured to use Elasticsearch, a search engine based on the Lucene library, but it could be configured to use any search engine. (Note: the Azure demonstration deployment will search only the stratified random sample dataset ("SRS Dataset") described in the paper cited above, with sentences curated only in the decision section headed "REASONS AND BASES FOR FINDINGS AND CONCLUSIONS." The Azure deployment is without communication to LA-Pad (see above).)

Search for Sentences by Keywords and Phrases

Filter based on Sentence type

Link to Paragraph and Case Context

Get In Touch

Clone the Repo to get Started. /github.com/LegalApprentice

Clone the Repo to get Started. Watch 5 min YouTube Demo

Questions? Need help? Contact Me.

stephen.strongiot@gmail.com