# Graph based Question Answering System

Source: [Graph based Question Answering System](<https://www.sota2.com/research/paper/68fa651d1e209131cea086d1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:19:52.933Z

Authors: Piyush Mital, Saurabh Agarwal, Bhargavi Neti, Yashodhara Haribhakta, Vibhavari Kamble, Krishnanjan Bhattacharjee, Debashri Das, Swati Mehta, Ajai Kumar

Published: 2018-12-05T06:31:48.000Z

## Abstract

In today's digital age in the dawning era of big data analytics it is not the information but the linking of information through entities and actions which defines the discourse. Any textual data either available on the Internet off off-line (like newspaper data, Wikipedia dump, etc) is basically connect information which cannot be treated isolated for its wholesome semantics. There is a need for an automated retrieval process with proper information extraction to structure the data for relevant and fast text analytics. The first big challenge is the conversion of unstructured textual data to structured data. Unlike other databases, graph databases handle relationships and connections elegantly. Our project aims at developing a graph-based information extraction and retrieval system.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1812.01828>)

[PDF](<https://arxiv.org/pdf/1812.01828.pdf>)