Readings for Jan. 27

As a refresher I read,

"Comparing Semantic Role Labeling with Typed Dependency Parsing in

Computational Metaphor Identification"

http://www.aclweb.org/anthology/W/W10/W10-0303.pdf

First off, the focus paper was slightly different than what I expected. Not that it was a bad read, but it seemed more like a general history of solving the metaphor problem and the current state of things. A lot easier to read than normal papers, and it presents some really interesting work, namely MIDAS, which I thought presented a very smart approach to the problem. Generally speaking, I feel like aggregating a huge repository of hand-generated metaphors isn't really the most elegant solution to the problem, which I guess not only emphasizes the difficulty of the problem itself, but the question of whether there's some slick solution to "successfully" triumphing over metaphor detection and resolution.

The additional paper I read attempted to use semantic role labeling in pace of typed dependency parsing to improve CMI, which is an approach that aims to identify patterns that indicate metaphors, and not worry so much about actually identifying each metaphor. I suppose you could call it a higher-order version of metaphor detection. Unfortunately, the paper doesn't have much to report in terms of result. Much of the paper was spent asking questions and giving background rather than actually talking about the significance of the research. It turns out that semantic role labeling proves slightly more effective in extracting relationships that have more semantic importance, but it's a double edged sword in that the granularity may be too fine to prove of effective use for input into other systems.

-Alan