Diego De Cao


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Robust and Efficient Page Rank for Word Sense Disambiguation
Diego De Cao | Roberto Basili | Matteo Luciani | Francesco Mesiano | Riccardo Rossi
Proceedings of TextGraphs-5 - 2010 Workshop on Graph-based Methods for Natural Language Processing

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Extensive Evaluation of a FrameNet-WordNet mapping resource
Diego De Cao | Danilo Croce | Roberto Basili
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Lexical resources are basic components of many text processing system devoted to information extraction, question answering or dialogue. In paste years many resources have been developed such as FrameNet and WordNet. FrameNet describes prototypical situations (i.e. Frames) while WordNet defines lexical meaning (senses) for the majority of English nouns, verbs, adjectives and adverbs. A major difference between FrameNet and WordNet refers to their coverage. Due of this lack of coverage, in recent years some approaches have been studied to make a bridge between this two resources, so a resource is used to extend the coverage of the other one. The nature of these approaches leave from supervised to supervised methods. The major problem is that there is not a standard in evaluation of the mapping. Each different work have tested own approach with a custom gold standard. This work give an extensive evaluation of the model proposed in (De Cao et al., 2008) using gold standard proposed in other works. Moreover this work give an empirical comparison between other available resources. As outcome of this work we also release the full mapping resource made according to the model proposed in (De Cao et al., 2008).


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Towards a Vector Space Model for FrameNet-like Resources
Marco Pennacchiotti | Diego De Cao | Paolo Marocco | Roberto Basili
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In this paper, we present an original framework to model frame semantic resources (namely, FrameNet) using minimal supervision. This framework can be leveraged both to expand an existing FrameNet with new knowledge, and to induce a FrameNet in a new language. Our hypothesis is that a frame semantic resource can be modeled and represented by a suitable semantic space model. The intuition is that semantic spaces are an effective model of the notion of “being characteristic of a frame” for both lexical elements and full sentences. The paper gives two main contributions. First, it shows that our hypothesis is valid and can be successfully implemented. Second, it explores different types of semantic VSMs, outlining which one is more suitable for representing a frame semantic resource. In the paper, VSMs are used for modeling the linguistic core of a frame, the lexical units. Indeed, if the hypothesis is verified for these units, the proposed framework has a much wider application.

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Combining Word Sense and Usage for Modeling Frame Semantics
Diego De Cao | Danilo Croce | Marco Pennacchiotti | Roberto Basili
Semantics in Text Processing. STEP 2008 Conference Proceedings

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Automatic induction of FrameNet lexical units
Marco Pennacchiotti | Diego De Cao | Roberto Basili | Danilo Croce | Michael Roth
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing