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.