MAS.632 Conversational Computer Systems - MIT OpenCourseWare

190 VOICE COMMUNICATION WIIH (OMPUTIRS
Knwledge Representaion
ANIMATEI
Figure 9.10. A semantic network including both a type hierarchy (ovals)
and ease grammar (squares) categories. After [Allen], p. 209.
To understand what a person intends by an utterance we need to employ knowledge
about the world and the objects in it being referred to by the sentence. For
example, to interpret "It's a bit too breezy in here" as a request to close the window
of a car, we need to know that a breeze is motion of air, that solid objects
block the flow of air,and that windows are solid objects that can be closed by some
mechanism such as a crank or motor. A knowledge representation provides a
means to store and computationally access information about the world, which
may be general facts (although windows are clear, they can close an opening) or
details of a specific current situation (the car window is open, and the crank will
close it).
Knowledge representation systems contain two components, a knowledge
base and the inference engine. A knowledge base is a database containing
facts about the world or information about a situation, and the inference
engine operates on the knowledge base according to a set of rules. Inference
may be primarily declarative or procedural, depending on whether it
stresses the knowledge database or the inference operations to draw conclu­