The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical resources such as WordNet and Cyc. The current state...
This paper presents a semantic labeling technique based on information encoded in FrameNet. Sentences labeled for frames relevant to any new Information Extraction domain enable t...
Alessandro Moschitti, Paul Morarescu, Sanda M. Har...
We define a denotational semantics for Light Affine Logic (LAL) which has the property that denotations of functions are polynomial time computable by construction of the model. Th...
We show that we can automatically classify semantically related phrases into 10 classes. Classification robustness is improved by training with multiple sources of evidence, inclu...
Ben Carterette, Rosie Jones, Wiley Greiner, Cory B...