Computational
Models of
Discourse Analysis
Carolyn Penstein Rosé
Language Technologies Institute/
Human-Computer Interaction Institute
Computational Approaches

Two steps
Examples from the paper:
 Step
1: Metaphor
recognition
 Step 2: Metaphor
interpretation

Does this paradigm
cover everything that
Lakoff and Johnson
place under the
heading of metaphor?
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
Announcements!
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Questions about presentations for next
time?
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Rearranged syllabus slightly: see Drupal
Posted responses to posts
Readings for next unit + most of rest of semester posted
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Next unit focuses on Sentiment Analysis
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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!
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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
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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
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Talking Points 2008: uses WordNet, then uses minimal
edits to bridge concepts
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Narayan’s KARMA 2004: parsed text as input
Barnden and Lee’s ATT-Meta 2007: logical forms as input
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?
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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

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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
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
metaphor is on uncovering the literal
meaning of expository text.
Another spin on Metaphor
Recognition
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Perspective modeling work
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Different computational approach
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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
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Liberal versus Conservative
Pro or Against
Sentiment analysis more generally
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?