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Automatic Question Generation

Post · Apr 7, 2017 15:29 ·

squad sequence-to-sequence cs-cl

Looking for ways to generate a FAQ from your docs? This paper points to a potential direction.

Highlights From the Paper

  • “Sentence-answer-question triples as our training, development and test sets”
  • “The proposed approach uses a feature rich encoder to encode answer position, POS and NER tag information”

Datasets

Arxiv Abstract

  • Qingyu Zhou
  • Nan Yang
  • Furu Wei
  • Chuanqi Tan
  • Hangbo Bao
  • Ming Zhou

Automatic question generation aims to generate questions from a text passage where the generated questions can be answered by certain sub-spans of the given passage. Traditional methods mainly use rigid heuristic rules to transform a sentence into related questions. In this work, we propose to apply the neural encoder-decoder model to generate meaningful and diverse questions from natural language sentences. The encoder reads the input text and the answer position, to produce an answer-aware input representation, which is fed to the decoder to generate an answer focused question. We conduct a preliminary study on neural question generation from text with the SQuAD dataset, and the experiment results show that our method can produce fluent and diverse questions.

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