Online Inference-Rule Learning from Natural-Language Extractions

@inproceedings{Raghavan2013OnlineIL,
  title={Online Inference-Rule Learning from Natural-Language Extractions},
  author={Sindhu Raghavan and Raymond J. Mooney},
  booktitle={AAAI Workshop: Statistical Relational Artificial Intelligence},
  year={2013}
}
In this paper, we consider the problem of learning commonsense knowledge in the form of first-order rules from incomplete and noisy natural-language extractions produced by an off-the-shelf information extraction (IE) system. Much of the information conveyed in text must be inferred from what is explicitly stated since easily inferable facts are rarely mentioned. The proposed rule learner accounts for this phenomenon by learning rules in which the body of the rule contains relations that are… CONTINUE READING

Similar Papers

Loading similar papers…