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mittalpusa's Projects

goreact icon goreact

Example Go (backend) React (frontend) Application

gpt4free icon gpt4free

decentralising the Ai Industry, just some language model api's...

graphql-playlist icon graphql-playlist

All course files for the GraphQL tutorial playlist on The Net Ninja YouTube channel.

knowprompt icon knowprompt

Code and datasets for the WWW2022 paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction."

legal-document-similarity icon legal-document-similarity

Legal document similarity - Code, data, and models for the ICAIL 2021 paper "Evaluating Document Representations for Content-based Legal Literature Recommendations"

lesicin icon lesicin

Dataset and codes for the paper "LeSICiN: A Heterogeneous Graph-based Approach for Automatic Legal Statute Identification from Indian Legal Documents", accepted and to be published at AAAI 2022.

lillie icon lillie

OIE Triple Extractor for Database Integration

lmops icon lmops

General technology for enabling AI capabilities w/ LLMs and MLLMs

multimodal-deep-learning icon multimodal-deep-learning

This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.

ner-annotator icon ner-annotator

Named Entity Recognition (NER) Annotation tool for SpaCy. Generates Traning Data as a JSON which can be readily used.

ner-re icon ner-re

A Named Entity Recognition + Entity Linker + Relation Extraction Pipeline built using spacy v3. Given a text, the pipeline will extract entities from the text as trained and will disambiguate the entities to its normalized form through an Entity Linker connected to a Knowledge Base and will assign a relation between the entities, if any.

ontoimportsuite icon ontoimportsuite

The "OntoImportSuite" is a set of proof-of-concept tools to extract and process heterogeneous data from clinical system, like the electronic medical record. This data can be mapped and transformed to match a set of common data elements, which will then be exported into a target system (i2b2) for research purposes. The system uses OWL ontologies to store information about the source and target systems and the mapping and transformation knowledge. The OWL ontologies are then translated into SQL scripts to perform the data integration on the database level.

ontojena icon ontojena

java project for manipulating .owl ontologies using jena

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