PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

ADN-classifier: Automatically assigning denotation types to nominalizations
Aina Peris, Mariona Taulé, Gemma Boleda and Horacio Rodriguez
In: LREC 2010, 19-21 May 2010, Valletta, Malta.

Abstract

This paper presents the ADN-Classifier, an Automatic classification system of Spanish Deverbal Nominalizations aimed at identifying its semantic denotation (i.e. event, result, underspecified, or lexicalized). The classifier can be used for NLP tasks such as coreference resolution or paraphrase detection. To our knowledge, the ADN-Classifier is the first effort in acquisition of denotations for nominalizations using Machine Learning.We compare the results of the classifier when using a decreasing number of Knowledge Sources, namely (1) the complete nominal lexicon (AnCora-Nom) that includes sense distictions, (2) the nominal lexicon (AnCora-Nom) removing the sense-specific information, (3) nominalizations’ context information obtained from a treebank corpus (AnCora-Es) and (4) the combination of the previous linguistic resources. In a realistic scenario, that is, without sense distinction, the best results achieved are those taking into account the information declared in the lexicon (89.40% accuracy). This shows that the lexicon contains crucial information (such as argument structure) that corpus-derived features cannot substitute for.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:7500
Deposited By:Gemma Boleda
Deposited On:17 March 2011