Semantic Web Dog Food

Presented at: The Sixth International Language Resources and Evaluation Conference (LREC2008)

by Davide Picca, Alfio Massimiliano Gliozzo, Massimiliano Ciaramita

In this paper we present the procedure we followed to develop the Italian Super Sense Tagger. In particular, we adapted the English SuperSense Tagger to the Italian Language by exploiting a parallel sense labeled corpus for training. As for English, the Italian tagger uses a fixed set of 26 semantic labels, called supersenses, achieving a slightly lower accuracy due to the lower quality of the Italian training data. Both taggers accomplish the same task of identifying entities and concepts belonging to a common set of ontological types. This parallelism allows us to define effective methodologies for a broad range of cross-language knowledge acquisition tasks

Keywords: Acquisition, Machine Learning, Named Entity recognition, Tagging, Linguistics

Resource URI on the dog food server: http://data.semanticweb.org/conference/lrec/2008/papers/599

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