Open question answering over curated and extracted knowledge bases

@article{Fader2014OpenQA,
  title={Open question answering over curated and extracted knowledge bases},
  author={Anthony Fader and Luke Zettlemoyer and Oren Etzioni},
  journal={Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining},
  year={2014}
}
  • Anthony Fader, Luke Zettlemoyer, Oren Etzioni
  • Published 2014
  • Computer Science
  • Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
  • We consider the problem of open-domain question answering (Open QA) over massive knowledge bases (KBs). Existing approaches use either manually curated KBs like Freebase or KBs automatically extracted from unstructured text. In this paper, we present OQA, the first approach to leverage both curated and extracted KBs. A key technical challenge is designing systems that are robust to the high variability in both natural language questions and massive KBs. OQA achieves robustness by decomposing… CONTINUE READING
    333 Citations
    Never-Ending Learning for Open-Domain Question Answering over Knowledge Bases
    • 29
    • Highly Influenced
    • PDF
    Question answering over knowledge bases with continuous learning
    • Highly Influenced
    • PDF
    Hybrid Question Answering over Knowledge Base and Free Text
    • 30
    • PDF
    Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
    • 87
    • PDF
    Open Domain Question Answering via Semantic Enrichment
    • 93
    • Highly Influenced
    • PDF
    Question Answering from Unstructured Text by Retrieval and Comprehension
    • 14
    • PDF
    Paraphrase for Open Question Answering: New Dataset and Methods
    • 2
    • Highly Influenced
    • PDF
    Open Question Answering
    • 1
    • PDF