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.
|Number of pages||4|
|Publication status||Published - 2006|
|Event||5th International Conference on Language Resources and Evaluation, LREC 2006 - Genoa, Italy|
Duration: 2006 May 22 → 2006 May 28
|Conference||5th International Conference on Language Resources and Evaluation, LREC 2006|
|Period||06/5/22 → 06/5/28|