Generate knowledge graph from unstructured text

Parsinator turns structured and unstructured text into a header-detail representation

Template for an AI application that extracts the job information from a job description using openAI functions and langchain

A small tool to normalize and extract values from unstructured text messages.

Unstructured data refers to information that is not organised using a predetermined data model or schema and cannot be stored in a conventional relational database system. There are several methods for search unstructured data semantically- That is by taking the actual context/meaning of the sentences.One best approach is index based approach.

Explore my Document Clustering and Theme Extraction project, offering effective tools for organizing and extracting valuable insights from extensive text datasets. The objective is to provide a systematic approach to comprehend and organize unstructured text data.

Normalizing multiple-row-record in a table (bank statement example). Getting a table with normalized records (one record corresponds to one row)

Get a structured table with the ability to sort and filter data (for simple office use) from text heap of PDF bank statement

A chatbot and accompanying utilities for quickly making sense of and getting answers about large, unstructured corpora.

This ChatBot was implemented using NLTK (Natural Language ToolKit) with Python. ChatBot uses rule based retrieving of providing definitions to Machine Learning and Statistics terms based on user request. For simplicity, only few terms were added to the ChatBot response file