We would like to extract features that express information that is diverse and orthogonal to the one given by distributional similarity.
we turn to existing knowledge resources that were created using both manual and automatic methods, expressing various types of linguistic and statistical information that is relevant for entailment prediction: WordNet: contains manually annotated relations such as hypernymy, synonymy, antonymy, derivation, and entailment.