Reporting bias and knowledge acquisition

  title={Reporting bias and knowledge acquisition},
  author={Jonathan Gordon and Benjamin Van Durme},
  booktitle={AKBC '13},
  • Jonathan Gordon, Benjamin Van Durme
  • Published in AKBC '13 2013
  • Computer Science
  • Much work in knowledge extraction from text tacitly assumes that the frequency with which people write about actions, outcomes, or properties is a reflection of real-world frequencies or the degree to which a property is characteristic of a class of individuals. In this paper, we question this idea, examining the phenomenon of reporting bias and the challenge it poses for knowledge extraction. We conclude with discussion of approaches to learning commonsense knowledge from text despite this… CONTINUE READING
    82 Citations

    Tables and Topics from this paper

    Do Neural Language Models Overcome Reporting Bias?
    Commonsense Knowledge Mining from Pretrained Models
    • 50
    • PDF
    The Physics of Text: Ontological Realism in Information Extraction
    • 1
    • PDF
    Using natural language to integrate, evaluate, and optimize extracted knowledge bases
    • 3
    • PDF
    Inducing Relational Knowledge from BERT
    • 28
    • PDF
    Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
    • 1
    • PDF