Abstract
This paper proposes a hierarchical organization of the linguistic knowledge, that views grammar as an abstraction of item-dependent information (in particular, an abstraction of subcategorization frames into a hierarchy of classes). The formalism has been successfully applied to a classification of 105 Italian verbal frames, developed by analysing a corpus of about 500,000 words.
The proposed framework (expressed in a dependency approach) is of linguistic and computational interest. From a linguistic point of view, it is a clear, significant and non-redundant representation. From a computational point of view, structuring the grammar into a hierarchy allows to define a predictive component for parsing, exploiting the information at many levels of the hierarchy: this allows to reduce the ambiguity, a very big problem in large scale NLP systems.
We are indebted to Paola Merlo and Leonardo Lesmo for their precious support.
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Barbero, C., Lombardo, V. (1997). Wide-Coverage lexicalized grammars. In: Lenzerini, M. (eds) AI*IA 97: Advances in Artificial Intelligence. AI*IA 1997. Lecture Notes in Computer Science, vol 1321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63576-9_96
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DOI: https://doi.org/10.1007/3-540-63576-9_96
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