Eckhard Bick - VISL

co-ordination, are syntactically irresolvable. Such “surplus” ambiguity compromises
notational clarity and creates huge “parse forests”.
• 3. Since structure is found by recursive generation of syntactic trees, a lot of “dead
end” partial constructions are computed, rendering the technique very time
consuming (to the point of “time out” for very long sentences).
Furthermore, Generative Grammar assumes a stable language system with clear-cut
borders for what is correct. The objective is to generate “all and only” the sentences of a
given language that are correct. The Chomskyan point of departure was an innate and
trained “language faculty” rooted in the human brain and capable of making the
distinction by means of “competence”. This approach contains the risk of fostering a
“black-and-white”-attidude to language analysis, visible for instance when a generative
grammar’s rule set is seen as prescriptive in nature rather than descriptive (since it rules
out as “not part of the language system” or as “performance errors” what it cannot
describe). In general, the generative approach also entails that the notion of “parsing
failure” is acceptable 97 , whereas probabilistic and CG-based systems assume that “the
corpus is always right”, and can run on large chunks of running text without ever giving
up on a sentence.
When comparing Constraint Grammar to Generative Grammar, one has to distinguish
between conceptual differences and implementational differences. Conceptually, CG
is - unlike PSG - parsing-oriented and next to useless for generating sentences. In CG,
ambiguity is defined independently from structure, and ambiguity resolution is
consequently more flexible. CG is reductionist rather than generativist, which makes it
more tolerant (or robust) with regard to what Chomskyan grammar would call
performance failures, incomplete utterances, dialectal variation and the like. In its
objective, CG is descriptive rather than prescriptive, but technically, it follows a third
road, which - in analogy with the other two - might be termed “prohibitive”.
Implementationally, a key difference is that, in Constraint Grammar, ambiguity
can be reduced gradually, without retracing, and that rules tend to add or remove form
and function labels for individual words, defining (in a reductionist way) what is not
contextually feasible rather than expressing syntactic patterns (in a generative,
productive way) for multi-word units.
The performance of most grammar based systems is difficult to compare to that of
probabilistic or Constraint Grammar based parsers, since the theoretical potential is
usually valued higher than practical applicability to unrestricted text, for example by
trading lexical coverage for descriptive power. Still, such systems have been applied to
97 Though the programming formalism as such would allow compromise solutions like partial parses or automatic ad hoc
rule amendments.
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