Metaphors are ubiquitous in language and developing methods to identify and deal with metaphors is an open problem in Natural Language Processing (NLP). In this paper we describe results from using a maximum entropy (ME) classifier to identify metaphors. Using the Wall Street Journal (WSJ) corpus, we annotated all the verbal targets associated with a set of frames which includes frames of spatial motion, manipulation, and health. One surprising finding was that over 90% of annotated targets from these frames are used metaphorically, underscoring the importance of processing figurative language. We then used this labeled data and each verbal target’s PropBank annotation to train a maximum entropy classifier to make this literal vs. metaphoric distinction. Using the classifier, we reduce the final error in the test set by 5 % over the verb-specific majority class baseline and 31 % over the corpus-wide majority class baseline. 1

This paper presents a computational model of referential metaphor comprehension. This model is designed on top of Latent Semantic Analysis (LSA), a model of the representation of word and text meanings. Comprehending a referential metaphor consists in scanning the semantic neighbors of the metaphor in order to find words that are also semantically related to the context. The depth of that search is compared to the time it takes for humans to process a metaphor. In particular, we are interested in two independent variables: the nature of the reference (either a literal meaning or a figurative meaning) and the nature of the context (inductive or not inductive). We show that, for both humans and model, first, metaphors take longer to process than the literal meanings and second, an inductive context can shorten the processing time.

Due to the inherent abstract nature of certain types of software development, programmers and software engineers use metaphoric language throughout many areas of their work. This paper examines some of the many metaphors found within software development and engineering. A simplistic taxonomy is used to present the metaphors that have been found. The use and importance of metaphor and programming are discussed and some consideration is given towards the origins of metaphor. Intersections with other disciplines interested in this topic are also presented. It is concluded that software developers should ideally possess the ability to both understand and to generate new metaphors to successfully develop usable and successful software.