https://github.com/scionoftech/question_answering_system

Question answering system developed using seq2seq modeling - The SQuAD dataset.
https://github.com/scionoftech/question_answering_system

natural-language questions-and-answers rnn seq2seq squad-dataset

Last synced: about 2 months ago
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Question answering system developed using seq2seq modeling - The SQuAD dataset.

• Host: GitHub
• URL: https://github.com/scionoftech/question_answering_system
• Owner: scionoftech
• Created: 2019-12-28T16:14:24.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-12-28T17:00:39.000Z (over 5 years ago)
• Last Synced: 2025-03-25T19:21:23.450Z (2 months ago)
• Topics: natural-language, questions-and-answers, rnn, seq2seq, squad-dataset
• Language: Jupyter Notebook
• Size: 263 KB
• Stars: 9
• Watchers: 1
• Forks: 4
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# Question answering system

Question answering is a computer science discipline within the fields of information retrieval and natural language processing, which is concerned with building systems that automatically answer questions posed by humans in a natural language.

![qa.png](qa.png)

The objective here is to build a Question answering system using the seq2seq approach.

### SQuAD Dataset

Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.

We can download the dataset from [here](https://rajpurkar.github.io/SQuAD-explorer/)