Abstract. The paper introduces a method for interpreting novel noun compounds with semantic relations. The method is built around word similarity with pretagged noun compounds, based on WordNet::Similarity. Over 1,088 training instances and 1,081 test instances from the Wall Street Journal in the Penn Treebank, the proposed method was able to correctly classify 53.3% of the test noun compounds. We also investigated the relative contribution of the modifier and the head noun in noun compounds of different semantic types.
REF introduced a machine learning approach that used WordNet for classifying compounds based on abstract semantic relations.
Automatic Interpretation of Noun Compounds Using WordNet Similarity
Second International Joint Conference on Natural Language Processing: Full Papers
Computer Science