Labeling Semantically Motivated Clusters of Verbal Relations

Gabriela Ferraro , Leo Wanner


Document clustering is a popular research eld 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 signicant dierences 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 conrm this assumption, we
carry out a number of experiments and evaluate their outcome against baselines
and gold standard labeled clusters.

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