%0 Conference Proceedings %T Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences %A Inui, Kentaro %A Hirano, Toru %A Iida, Ryu %A Fujita, Atsushi %A Matsumoto, Yuji %Y Calzolari, Nicoletta %Y Choukri, Khalid %Y Gangemi, Aldo %Y Maegaard, Bente %Y Mariani, Joseph %Y Odijk, Jan %Y Tapias, Daniel %S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06) %D 2006 %8 May %I European Language Resources Association (ELRA) %C Genoa, Italy %F inui-etal-2006-augmenting %X One of the crucial issues in semantic parsing is how to reduce costs of collecting a sufficiently large amount of labeled data. This paper presents a new approach to cost-saving annotation of example sentences with predicate-argument structure information, taking Japanese as a target language. In this scheme, a large collection of unlabeled examples are first clustered and selectively sampled, and for each sampled cluster, only one representative example is given a label by a human annotator. The advantages of this approach are empirically supported by the results of our preliminary experiments, where we use an existing similarity function and naive sampling strategy. %U http://www.lrec-conf.org/proceedings/lrec2006/pdf/610_pdf.pdf