Computational Models of Discourse Analysis Carolyn Penstein Rosé Language Technologies Institute/ Human-Computer Interaction Institute Computational Approaches Examples from the paper: Two steps Step 1: Metaphor recognition Step 2: Metaphor interpretation Lakoff’s concept: Does this paradigm Metaphors structure how we think about an event or state. cover everything that The way we think affects: (A) what we expect to happen, Lakoff and Johnson (B) what we do, (C) how we respond to what occurs place under the during an event, (D) and how we talk about what we heading of metaphor? and others are doing Announcements! Questions about presentations for next time? Rearranged syllabus slightly: see Drupal Posted responses to posts Readings for next unit + most of rest of semester posted Next unit focuses on Sentiment Analysis Product review dataset will be ready by next Monday for Assignment 3 Note we won’t meet during Spring Break Unit 3 has a break too! We won’t meet on Wed, March 30 since several of us will be away MIP: Metaphor Identification Procedure Growing Interest? #References Automatic Approaches Recent Approaches to Detection Peters and Peters 2000: Mined wordnet for abstract concepts that share word forms such as publication-publisher Mason 2004: Mine an internet corpus for domain specific selectional restriction differences Birke and Sarkar 2006: Start with seed sentences that have been annotated with figurative versus literal, and then do something like an instance based learning approach Gedigan et al. 2006: extract frames for MOTION and CURE from FrameNet, then extract sentences related to these from PropBank. Annotate by hand for metaphoricity. Use a maximum entropy classifier. Krishnakumaran and Zhu 2007: Look for sentences with “be” verb. Check for hyponymy using WordNet. If not there, look at bigram counts of subj-obj. If not high, then might be metaphorical. What would Fass say? Problem with selectional restrictions as evidence: Will detect all kinds of nonliteral and anomalous language regardless if it is metaphorical or not Common metaphorical sense (i.e., “dead metaphors”) will fail here Some statements can be interpreted either way: “All men are animals” Recent Approaches to Interpretation Metaphor based reasoning framework – reason in a source domain and apply reasoning to the target domain using a conceptual mapping Narayan’s KARMA 2004: parsed text as input Barnden and Lee’s ATT-Meta 2007: logical forms as input Talking Points 2008: uses WordNet, then uses minimal edits to bridge concepts Makeup is the Western burqa Shutova 2010: uses a statistical paraphrase approach Shutova’s Take Away Message Approaches from the 80s and 90s were rule based Knowledge engineering bottleneck Shutova’s work give some evidence that metaphor can be handled using a more contemporary (i.e., machine learning) paradigms Cast the metaphor interpretation problem as a paraphrase problem so you can use statistical machine translation approaches Does paraphrase “cut it”? Do you see a metaphor here? * How much of the problem can be solved by paraphrase? Do you see metaphor here? Evey: Who are you? V: Who? Who is but the form following the function of what and what I am is a man in a mask. Evey: Well, I can see that. V: Of course you can, I’m not questioning your powers of observation, I’m merely remarking upon the paradox of asking a masked man who he is. Evey: Oh. V: But on this most auspicious of nights, permit me then, in lieu of the more commonplace soubriquet, to suggest the character of this dramatis persona. [pauses for a few seconds] Voila! In view humble vaudevillian veteran, cast vicariously as both victim and villain by the vicissitudes of fate. This visage, no mere veneer of vanity, is a vestige of the “vox populi” now vacant, vanished… Data’s Identity We see evidence of how Data is framing his identity. Do we see metaphor Note: The focus of the work of Shutova and here? others who have self-identified as working on metaphor is on uncovering the literal meaning of expository text. Lakoff’s concept: Metaphors structure how we think about an event or state. The way we think affects: (A) what we expect to happen, (B) what we do, (C) how we respond to what occurs during an event, (D) and how we talk about what we and others are doing Another spin on Metaphor Recognition Perspective modeling work Liberal versus Conservative Pro or Against Sentiment analysis more generally Different computational approach Skips step 1 – assumes all language represents perspective Simplifies step 2 – goal is to recognize a category rather than rephrase Usually models are based on word distributions Word vectors with weights Topic models We’ll explore this in the next unit Framing an Event in Progress Where does the paradigm for understanding metaphors break down with examples like this? Step 1: recognize metaphor Step 2: map to literal meaning *** Still understanding a concept/situation by comparison with another one Breaking the Paradigm What can we do with conversational data? How do we recognize that a metaphor is in play? What would it mean to do the interpretation? Questions?
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