Flexible Acquisition of Verb Subcategorization Frames in Italian

This paper describes a web-service system for automatic acquisition of verb subcategorization frames (SCFs) from parsed data in Italian. The system acquires SCFs in an unsupervised manner. We created two gold standards for the evaluation of the system, the first by mixing together information from two lexica (one manually created and the second automatically acquired) and manual exploration of corpus data and the other annotating data extracted from a specialized corpus (domain environment). Data filtering is accomplished by means of the maximum likelihood estimate (MLE). In addition to this, we assign to the extracted entries of the lexicon a confidence score and evaluate the extractor on domain specific data. The confidence score will allow the final user to easily select the entries of the lexicon in terms of their reliability.