PAC - a statistical clustering software for multi-dimensional clusters
- Type
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Tool
- Author
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Helmut Schmid
- Description
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PAC is a predicate-argument clustering software that is trained on predicate-frame-argument tuples and outputs a multi-dimensional cluster analysis, including clusters for the predicates and selectional preference abstraction over the predicate arguments.
PAC is trained on tuples such as
2 abandon SUBJ:NP company project 1 abstain SUBJ legislator 1 accede SUBJ:P:NP government to pact and induces a statistical soft clustering of these (and other) tuples.
- Reference
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Sabine Schulte im Walde, Christian Hying, Christian Scheible and Helmut Schmid: Combining EM Training and the MDL Principle for an Automatic Verb Classification Incorporating Selectional Preferences. In: Proceedings of ACL-HLT 2008. Columbus, Ohio.
- Download
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The PAC pages are maintained by Helmut Schmid.
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