Unsupervised Labeling of Noun Clusters
Semantic knowledge is important in many areas of
natural language processing. We propose a new
unsupervised learning algorithm to annotate groups
of nouns with hypernym labels. Several variations
of the algorithm are presented, including a method
that utilizes semantic information from WordNet.
The algorithm's results are compared against an
independently-developed labeling method. The
evaluation is performed using labels assigned to
noun clusters by several participants of a
specially designed human study.