Pegah Alipoormolabashi author Sabine Schulte im Walde author 2020-jul text Association for Computational Linguistics Seattle, USA conference publication Predicting the degree of compositionality of noun compounds is a crucial ingredient for lexicography and NLP applications, to know whether the compound should be treated as a whole, or through its constituents. Computational approaches for an automatic prediction typically represent compounds and their constituents within a vector space to have a numeric relatedness measure for the words. This paper provides a systematic evaluation of using different vector-space reduction variants for the prediction. We demonstrate that Word2vec and nouns-only dimensionality reductions are the most successful and stable vector space reduction variants for our task. alipoormolabashi-schulte-im-walde-2020-variants 2020-jul 51 54