CS
337 -- Intro
to Semantic Information Processing-- L. Birnbaum
LECTURE
6: REPRESENTING CONNECTED TEXT:
INFERENCE AND CAUSAL CHAINS
Returning to Rieger's theory of inference: let's
write some inference
molecules.
ENABLEMENT
molecule for ATRANS:
(ATRANS Actor (X) Object (Y) To (Z) From (W))
Build (HAS-POSSESSION Actor ( ) Object ( ))
Fill Actor with From of input
ATRANS
Object
with Object
Establish ENABLES link from this HAS-POSSESSION to the ATRANS
CAUSATIVE
molecule for HAS-POSSESSION:
(HAS-POSSESSION Actor (W) Object (Y))
Build (ATRANS Actor ( ) Object ( ) To ( ) From ( ))
Fill To with Actor of input HAS-POSSESSION
Object
with Object
Fill rest of cases with UNSPECIFIED
Establish RESULTS link from this ATRANS to the HAS-POSSESSION
Another example:
John
went over to the telephone.
RESULTATIVE:
John is at location of telephone.
MOTIVATIONAL:
John wants to be at location of telephone.
FUNCTION:
John wants to communicate something to somebody.
Part
of FUNCTION molecule for WANT:
(WANT Actor (X) (HAS-LOCATION Object (Y) Loc (Z)))
If Y is human (often X=Y)
and Z is (LOCATION-OF
Object (W))
and W has FUNCTION
FOO
then
Build (WANT
Actor ( ) (FOO))
Fill Actor of
WANT with ACTOR of input WANT
Fill Actor of
FOO with Object of HAS-LOCATION
Establish
INITIATE link between this WANT and input WANT
telephone
FUNCTION = (MTRANS Actor (X) Object ( ) to ( ) From (X))
and (MTRANS
Actor ( ) Object ( ) to (X) From ( ))
(You might need ACTION-PREDICTION inferences as well
to handle the
examples I gave.)
The important thing about inference is that it
enables us to EXPLAIN
what we read by constructing causal connections
between events and
situations described in text.
This leads us to the following theory
of text representation (Schank, 1975):
The
proper conceptual representation of a text describing an event
consists
not only of representations of the actions, states, and
objects
described therein, but also of causal connections between
these
entities, linking the text into a causally coherent chunk --
in
the simplest case, a CAUSAL CHAIN.
Compare the following example texts:
Mary
gave John a million dollars. He
bought a new car.
Mary
gave John a million dollars. She
visited her aunt in
Milwaukee.
What other theories of text representation might
there be?
Undifferentiated
links, i.e., causality is not special.
But
now consider:
John is married to Sally. The
boss called John into his
office. John's boss is a
Rosicrucian. The Rosicrucians are a
quasi-religious mystical organization.
Sally does not belong
to the Rosicrucians. Sally's
mother lives in Des Moines.
Let's look at a tough example:
Menakretes'
wife left for the country. Within a
week, one of the
slave
girls was wearing a new necklace.
Rieger's theory can't handle this kind of thing: if
inference chains
get too long, combinatorial problems arise in a big
way. But it CAN
handle the simpler examples.