@InProceedings{pado-EtAl:2016:COLING,
  author    = {Pad\'{o}, Sebastian  and  Herbelot, Aur\'{e}lie  and  Kisselew, Max  and  \v{S}najder, Jan},
  title     = {Predictability of Distributional Semantics in Derivational Word Formation},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {1285--1296},
  abstract  = {Compositional distributional semantic models (CDSMs) have successfully been
	applied to the task of predicting the meaning of a range of linguistic
	constructions. Their performance on semi- compositional word formation process
	of (morphological) derivation, however, has been extremely variable, with no
	large-scale empirical investigation to date. This paper fills that gap,
	performing an analysis of CDSM predictions on a large dataset (over 30,000
	German derivationally related word pairs). We use linear regression models to
	analyze CDSM performance and obtain insights into the linguistic factors that
	influence how predictable the distributional context of a derived word is going
	to be. We identify various such factors, notably part of speech, argument
	structure, and semantic regularity.},
  url       = {http://aclweb.org/anthology/C16-1122}
}