Labeling Semantically Motivated Clusters of Verbal Relations

Document clustering is a popular research field in Natural Language Processing, Data Mining and Information Retrieval. The problem of lexical unit (LU) clustering has been less addressed, and even less so the problem of labeling LU clusters. However, in our application that deals with the distillation of relational tuples from patent claims as input to block diagram or a concept map drawing programs, this problem is central. The assessment of various document cluster labeling techniques lets us assume that despite some significant differences that need to be taken into account some of these techniques may also be applied to verbal relation cluster labeling we are concerned with. To confirm this assumption, we carry out a number of experiments and evaluate their outcome against baselines and gold standard labeled clusters.