Esther König

A description language for syntactically annotated corpora

This paper introduces a description language for syntactically annotated corpora which allows for encoding both the syntactic annotation to a corpus and the queries to a syntactically annotated corpus.In terms of descriptive adequacy and computational efficiency, the description language is a compromise between script-like corpus query languages and high-level, typed unification-based grammar formalisms.

Fibred semantics for feature-based grammar logic

This paper gives a simple method for providing categorial brands of feature-based unification grammars with a model-theoretic semantics. The key idea is to apply the paradigm of fibred semantics (or layered logics, see Gabbay (1990)) in order to combine the two components of a feature-based grammar logic. We demonstrate the method for the augmentation of Lambek categorial grammar with Kasper/Rounds-style feature logic. These are combined by replacing (or annotating) atomic formulas of the first logic, i.e. the basic syntactic types, by formulas of the second. Modelling such a combined logic is less trivial than one might expect. The direct application of the fibred semantics method where a combined atomic formula like np (num: sg & pers: 3rd) denotes those strings which have the indicated property and the categorial operators denote the usual left- and right-residuals of these string sets, does not match the intuitive, unification-based proof theory. Unification implements a global bookkeeping with respect to a proof whereas the direct fibring method restricts its view to the atoms of the grammar logic. The solution is to interpret the (embedded) feature terms as global feature constraints while maintaining the same kind of fibred structures. For this adjusted semantics, the anticipated proof system is sound and complete.

A General Reasoning Scheme for Underspecified Representations

Underspecified semantic representations have attracted increasing interest within computational linguistics. Several formalisms have been developed that allow to represent sentence or text meanings with that degree of specificity that is determined by the context of interpretation. As the context changes they must allow for (partial) disambiguation steps performed by a process of refinement that goes hand in hand with the construction algorithm. And as the interpretation of phrases often1 relies on deductive principles and thus any construction algorithm must be able to integrate the results of deductive processes, any semantic formalism should be equipped with a deductive component that operates directly on its semantic forms.

An Efficient Decision Algorithm for Feature Logic

Feature terms are a common denominator of basic data-structures in knowledge representation and computational linguistics. The adaptation of the usual unification algorithms for first order terms is not straightforward, because feature terms may contain logical disjunction. Expansion into disjunctive normal form would reduce the problem more or less to unification of first order terms. But for reasons of efficiency, rewriting into disjunctive normal form should not be compulsory. In this paper, a sequent calculus is defined which gives a clear formal basis for proof optimizations: inference steps which require more than one subproof, i.e. which lead towards a “disjunctive normal form”, are only performed when they are no longer unavoidable. It is shown that the calculus is sound and complete with respect to the so-called feature structure interpretations of feature terms.