Papers › Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types

Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types

19 Feb 2018NAACL 2018 6arXiv:1802.06842archive 2025-07-28

Hady Elsahar, Christophe Gravier, Frederique Laforest

We present a neural model for question generation from knowledge base triples in a "Zero-Shot" setup, that is generating questions for triples containing predicates, subject types or object types that were not seen at training time. Our model leverages triples occurrences in the natural language corpus in an encoder-decoder architecture, paired with an original part-of-speech copy action mechanism to generate questions. Benchmark and human evaluation show that our model sets a new state-of-the-art for zero-shot QG.

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