Abstract
Lexical blending is a highly productive and frequent process by which new words enter a language. A blend is formed when two or more source words are combined, with at least one them shortened, as in brunch (breakfast+lunch). We use linguistic and cognitive aspects of this process to motivate a computational treatment of neologisms formed by blending. We propose statistical features that can indicate the source words of a blend, and whether an unknown word was formed by blending. We present computational experiments that show the usefulness in these tasks of features tapping into the recognizability of the source words in the blend, in combination with their semantic properties.
Users
Please
log in to take part in the discussion (add own reviews or comments).