Abstract
The paper introduces a method for interpreting novel noun compounds with semantic relations. The method is built around word similarity with pre-tagged 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.
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Kim, S.N., Baldwin, T. (2005). Automatic Interpretation of Noun Compounds Using WordNet Similarity. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_82
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DOI: https://doi.org/10.1007/11562214_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29172-5
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