For this week, I selected the paper:
A Fluid Knowledge Representation for Understanding and Generating Creative Metaphors
Tony Veale and Yanfen Hao
The authors present a conceptual representation based on the idea of a slipnet, wherein concepts are fluidly connected using information from WordNet and the World Wide Web. Talking Points of the form is_ADJ:NOUN and VERB:NOUN are automatically extracted from parses of WordNet dictionary glosses for lexical concepts. For example, talking points for "Hamas" could include "is_political:movement" and points for "musician" could include "composes:music". Additional talking points are gathered from the Web using customized search queries to detect attributes of the form has_ADJ:facet, such as "has_magical:skill" for "Wizard". Once talking points are associated with concepts, a slipnet can be constructed by linking points that are semantically related according to WordNet. For example, we can follow the path "composes:music" (attribute of "composer") to "composes:speech", "writes:speech", and finally "writes:novel" (attribute of "author") to see that composer is semantically related to author. This approach is particularly interesting for metaphor interpretation in that it offers both a method for detecting that words are semantically similar in ways that are not directly obvious (not first-order related in WordNet) as well as a measure of the "slippage" between them (number of steps in the slipnet to relate one to the other).