From: AAAI Technical Report WS-93-05. Compilation copyright © 1993, AAAI (www.aaai.org). All rights reserved.
Consistency
Hidde
of scientific
knowledge bases
(Extended abstract)
de Jong,
Nicolaas
J.I.
Mars and Paul E. van der
Knowledge-based
Systems Group, University
of Twente
P.O. Box 217, 7500 AE Enschede,
The Netherlands
Vet
Approach
Abstract
Let A be a set of knowledge, expressed in the form
of propositions. Then A is inconsistent iff there is a
proposition a such that A t- a and A ~- -~a. Consistency in this rigorous form is rare in scientific and engineering domains. A more useful notion is that of local
consistency. A is called locally consistent iff there is a
set of predefined subsets of A such that every subset
is consistent. A is said to contain at least one conflict
iff A is locally consistent but (globally) inconsistent.
This state of affairs can be called normal.
Various justification
relations hold between the
propositions in A; together they form a justification
structure. A proposition may deductively follow from
another proposition or set of propositions and thus be
justified; a set of particular propositions mayinductively justify a more general proposition; and so on.
By inspecting the justification structure, theories can
be identified as sets of propositions that are coherent
by particular justification relations. The classical example of a scientific conflict arises by taking a theory
(including its supporting observations) as a predefined
subset of A and adding an observation contradicting
the theory to A.
The conflict turns into a local inconsistency by
adding the contradicting observation to the theory’s
justification structure. The local inconsistency can be
solved by further transformations of the justification
structure. This solution is not always possible.
To systematize the many transformations which can
be used to resolve inconsistencies, a list of primitive
revision actions has been established. A primitive revision action changes a piece of knowledgein the justification structure. Consequently, it mayoccasion the
need to modify the justifications
and/or apply new
primitive revision actions.
The primitive revision actions identified have been
organized in a tree structure. Examples of primitive
revision actions are specialize the antecedent of a conditional expression by adding a conjunct and reject a
law. Primitive revision actions can be combined into
composite revision actions.
Our ideas about inconsistency resolution have been
The Plinius-project at the University of Twenteis
aimed at constructing large-scale knowledgebases
in scientific
and engineering domains, through
computer analysis of natural-language texts. One
of the many problems in this endeavor is caused
by inconsistencies in the scientific literature.
In this short report (of which a fuller version is
available [de Jong, 1992]) we describe our approach to the resolution of inconsistencies in largescale scientific and engineering knowledgebases.
Setting
Knowledge-based systems need large amounts of
knowledge to show passable competence. Acquiring
this knowledge using currently popular techniques is
time-consuming and slow. Knowledge acquisition is
seen as a major impediment to the development of capable knowledge-based systems.
For applications in science and engineering, most of
the knowledge required is available in books and, in
particular, in scientific journal articles. Unfortunately,
this knowledge is expressed in natural language, and
thus not immediately usable in knowledge-based systems.
The Plinius-project at the University of Twente is
aimed at constructing large-scale knowledge bases in
scientific and engineering domains, through computer
analysis of natural-language texts, in particular scientific journal articles[Mars and van der Vet, 1990].
Rather than analysing the full text of these documents
(which is infeasible at the current state-of-the-art),
use abstracts of journal articles. Abstracts are shorter
and more to the point than the full articles; they do
not normally contain illustrations.
One of the manyproblems in this endeavor is caused
by inconsistencies in the scientific literature.
This
problem is exacerbated by our use of abstracts: many
of the more subtle points of articles are lost in abstracts, thus causing spurious inconsistencies.
In the present article, we describe our approach to
the inconsistency problem.
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Literature
References
realized in an initial Prolog implementationof the justification structure and associated primitive revision
actions. For a full description of the underlying theory
and the implementation, we refer the reader to the full
report[de Jong, 1992].
A case
de Jong, Hidde 1992. Inconsistency resolution in
knowledge integration. M.Sc. thesis, University of
Twente, Department of Computer Science, Enschede,
The Netherlands.
Mars, N.J.I. and van der Vet, P.E. 1990. A semiautomatically generated knowledgebase for direct answers to user questions. In Czap, H. and Nedobity,
W., editors, Terminology and knowledge engineering.
Proceedings 2nd International Congress on Terminology and Knowledge Engineering Applications, Trier.
Indeks Verlag, Frankfurt am Main. 352-362.
study
To illustrate the issues in our approach to inconsistency resolution in scientific and engineering domains,
we carried out a case study in a small, but controversial domain: the cause of the mass extinction of the
dinosaurs.
This domain seems well-suited.
There are indeed
inconsistencies in the form of mutually incompatible
explanations of the extinction. The explanations have
been phrased by their proponents in reasonably precise
theories. There is a rather uniform and accepted terminology in the field, preventing inconsistencies through
mere terminological confusion. Unreliability of observations is not believed to be a main source of inconsistency. Finally, the amount of background knowledge
to obtain simple examples of inconsistencies is rather
limited.
Through analysis of abstracts of scientific journal
articles on the topic of the mass extinction of the dinosaurs, a justification structure for one particular explanation of the phenomenon,the Alvarez theory, tlas
been developed. The Alvarez theory attributes the extinction to the impact of a large body, an asteroid.
Simplified, this structure contains observations (e.g.,
high iridium concentration has been found in Northern
NewMexico in a layer corresponding to the assumed
time of the impact of the asteroid); backgroundknowledge (e.g., high iridium concentrations typically signify
asteroid impact); hypotheses (e.g., an asteroid impact
occurred at the boundary between the Tertiary and the
Cretaceous, that is 65 million years ago).
This structure, in combination with others describing other aspects of the theory, proved to help determine where exactly competing explanations of the
same phenomenoncontradict each other, suggest ways
to solve conflicts, and find out consequences of proposed modifications of the justification structure.
Conclusions
The approach involving local consistency and the use
of justification structures can be used, first, to detect
inconsistencies, at as low a level of detail as possible. Second, the structure allows the determination
of transformations that can reconcile the conflicts, by
proposing modifications to the theories. It helps suggest observations which can be done to corroborate
or contradict parts of the theories. It can also help
in finding specialisations of statements in the theories
that remove an apparent inconsistency.
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