A Latent Dirichlet Allocation Method for Selectional Preferences

@inproceedings{Ritter2010ALD,
  title={A Latent Dirichlet Allocation Method for Selectional Preferences},
  author={Alan Ritter and Mausam and Oren Etzioni},
  booktitle={ACL},
  year={2010}
}
The computation of selectional preferences, the admissible argument values for a relation, is a well-known NLP task with broad applicability. We present LDA-SP, which utilizes LinkLDA (Erosheva et al., 2004) to model selectional preferences. By simultaneously inferring latent topics and topic distributions over relations, LDA-SP combines the benefits of previous approaches: like traditional class-based approaches, it produces human-interpretable classes describing each relation's preferences… CONTINUE READING

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  • Our experiments demonstrate that LDA-SP significantly outperforms state of the art approaches obtaining an 85% increase in recall at precision 0.9 on the standard pseudodisambiguation task.

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