Àíäðóñ³â Í. Î.
×åðí³âåöüêèé
íàö³îíàëüíèé óí³âåðñèòåò
³ì. Þ. Ôåäüêîâè÷à
“Ô³ëîëîã³÷í³ íàóêè”:
Åòíî-, ñîö³î- ³ ïñèõîë³íãâ³ñòèêà
Knowledge representation and knowledge processing using frames
Recent work in computational
semantics has argued that the representation of meaning should not be
restricted to simple word definitions [3, 134]. "Background
knowledge" [4, 27] has to be included into these representations. The main
aim of the knowledge representation system described here is to find a
structure for this additional knowledge.
Knowledge related to words, but also
to nonlexicalized items, can be stored in frames. In our
system, slot names indicate different aspects under which an object can be
seen, e. g. appearance, character,
sociocultural norms. The values of these "super-slots"
are represented in subslots with NPs as their names and VPs as their slot
values. The use of verbs allows the encoding of many different relationships
between the frame concept and the concepts represented by slot names.
In our frame system, single inheritance is used. However,
unrestricted inheritance can result in a problematical information load at lower levels of the hierarchy. For
example, if we consider that a Person
is a kind of Organism, then Persons – according to
Konerding – should inherit nearly 30
superslots by Organism, define another 11
superslots for themselves, and – represented
in a frame system like ours – fill all
these with lists of subslots as answers to the superslot- "questions".
Different frames can be chosen for a
given item depending on context. The selected frame will then supply only the
background knowledge needed in the particular situation. Konerding
distinguishes two general frames for persons, the first one applying to persons
in a certain state or with a certain property, the second one applying to
persons with a certain profession. Minsky describes two frames for representing
a generator from different viewpoints, the mechanical and electrical
"subframes". This knowledge of the different roles people and objects
can play is stored in frames called noun
roles here. Every frame can be attached to a role slot of another
frame as a noun role, and any role can be instantiated for itself like any
other frame.
With respect to individual objects, this architecture
allows the creation of an object (e. g. a Person) to which one or more roles can be
attached dynamically (e.g. Politician
and French Person).
The object does not lose its identity (e. g. if we have named our person
Jacques Chirac, this information is stored at the initial (person) level, so
the name of the person remains Jacques Chirac whether we view him as a
Frenchman or as a politician). The roles of the object can be viewed and
compared independently. As the slot values of the role slots indicate the
context in which the person or object plays the particular role, we will no
longer be confronted with all the knowledge about the object at once.
At the class level, this architecture allows classes to provide
one or more default roles for the neutral or non-specified context, and special
roles for special contexts. Information overload caused by inheritance can thus
be avoided by treating the information formerly contained in some slots as a
noun role and only accessing it if necessary. For example, an Organism could have a role with the
frame Self Reproducing Organism which stores all the information that would
otherwise have been assigned to a reproduction
superslot. Instead of inheriting that superslot without
restrictions, the Person subclass
will inherit the Self Reproducing Organism as a role. It can also convert it to a subtype of Self Reproducing
Organism, e. g. Self Reproducing Person, filled
with more human-specific information.
Research relying on a newspaper
corpus showed that nation frames (Italian, Frenchman, German)
focused on quite different subslots when analysed in a
politico-economical context than they did in a neighbourhood or family context
like the one analysed by van Dijk. For example,
in the family context it is relevant what people eat and when and how they do
that. In the state context, however, it is important what people think about
politics, inflation, or national identity.
Consequently, the context has
to be taken into account when frames are established for the frame system. As
it is difficult to find a "neutral" context for a given word to
occur, a concept or word is first analysed in different "special"
contexts which are determined by key words and will yield different role frames
of the concept. It can then be decided whether some of the slots of these role
frames should be represented in the concept frame itself and/or whether one or
more roles should be regarded as default roles.
Accordingly, the world
knowledge stored in the frames and in the noun roles could be accessed by a
text understanding system. The structure of the frames can also be exploited
for other purposes like finding out resemblances between concepts, objects or
some of their aspects (slots, roles), or discovering structural regularities of
metonymies or metaphors.
References:
1. Dijk, Teun A.
van. Communicating
racism. Ethnic
prejudice in thought and talk. –
2. Konerding, Klaus-Peter. Frames und
lexikalisches Bedeutungswissen. Untersuchungen zur linguistischen Grundlegung einer Frametheorie und
zu ihrer Anwendung in der Lexikographie. – Tubingen:
Niemeyer, 1993 . – 298 p.
3. Minsky, Marvin. A framework for representing knowledge. The psychology of computer
vision. – New
York et al.: McGraw-Hill, 1975. – P. 211-277.
4. Pustejovsky,
James. The Generative Lexicon.
5. Yeap,
Wai-Kiang. A Sketched Computational Theory of Language
Comprehension. // Proceedings
of the Twentieth Annual Conference of the Cognitive Science Society. –