Knowledge Completion for Generics using Guided Tensor Factorization

@article{Sedghi2016KnowledgeCF,
  title={Knowledge Completion for Generics using Guided Tensor Factorization},
  author={Hanie Sedghi and Ashish Sabharwal},
  journal={Transactions of the Association for Computational Linguistics},
  year={2016},
  volume={6},
  pages={197-210}
}
Given a knowledge base or KB containing (noisy) facts about common nouns or generics, such as “all trees produce oxygen” or “some animals live in forests”, we consider the problem of inferring additional such facts at a precision similar to that of the starting KB. Such KBs capture general knowledge about the world, and are crucial for various applications such as question answering. Different from commonly studied named entity KBs such as Freebase, generics KBs involve quantification, have… CONTINUE READING
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