Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus

Understand

Over the past decade, large-scale supervised learning corpora have enabled machine learning researchers to make substantial advances.

• However, to this date, there are no large-scale question-answer corpora available.
• In this paper we present the 30M Factoid Question-Answer Corpus, an enormous question answer pair corpus produced by applying a novel neural network architecture on the knowledge base Freebase to transduce facts into natural language questions.
• The produced question answer pairs are evaluated both by human evaluators and using automatic evaluation metrics, including well-established machine translation and sentence similarity metrics.