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KGQA-leaderboard

Repository to track the progress in Question Answering over Knowledge Graphs (KGQA), including the datasets and the current state-of-the-art for the most common KGQA tasks.

The 30M Factoid Question-Answer Corpus

The 30M Factoid Question-Answer Corpus[1] is 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.

Leaderboard

References

[1] Serban, Iulian Vlad, Alberto García-Durán, Caglar Gulcehre, Sungjin Ahn, Sarath Chandar, Aaron Courville, and Yoshua Bengio. Generating factoid questions with recurrent neural networks: The 30m factoid question-answer corpus. arXiv preprint arXiv:1603.06807 (2016).

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