The idea is to be able to build a full fledged question answering system that can condense knowledge from uploaded pdf documents well enough to be able to answer a set of questions.

An android application which displays 'parts of speech' tags for questions entered using Apache's OpenNLP library(https://opennlp.apache.org/) .

Demo

Divide this into smaller cycles , a couple of objectives would be.

1. User is able to upload any pdf document.

• Introduce page limits if needed or assess how hard it is to upload pdfs.
• develop the entire interface to be able to upload a pdf in the application.

2. Simple question answering system on android to handle easy questions based on the knowledge that can be derived from the uploaded documents.

3. Refine the question answering system.

• Access the need for a knowledge graph or knowledge base of any kind.
• Specific section under references for refining question answering systems.

• Enter LLMs - develop a streamlit RAG app that allows users to upload documents and ask questions Done

1. Conversational question answering for alexa by amazon - https://www.amazon.science/publications/knowledge-informed-semantic-parsing-for-conversational-question-answering