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

  • author: Hady Elsahar, Christophe Gravier, Frederique Laforest
  • abstract: We present a neural model for question generation from knowledge graphs triples in a “Zero-shot” setup, that is generating questions for predicate, subject types or object types that were not seen at training time. Our model leverages triples occurrences in the natural language corpus in a encoder-decoder architecture, paired with an original part-of-speech copy action mechanism to generate questions. Benchmark and human evaluation show that our model outperforms state-of-the-art on this task.
  • keywords:
  • interpretation: OpenKG
  • pdf: paper
  • code: github
  • dataset: Freebase
  • ppt/video:
  • curation: Xiaoyu Shang