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Minimal recursion semantics (MRS) is a framework for computational semantics that is suitable for parsing and generation and that can be implemented in typed feature structure formalisms. We discuss why, in general, a semantic representation with minimal structure is desirable and illustrate how a descriptively adequate representation with a nonrecursive(More)
The LinGO (Linguistic Grammars Online) project's English Resource Grammar and the LKB grammar development environment are language resources which are freely available for download for any purpose, including commercial use (see http://lingo.stanford.edu). Executable programs and source code are both included. In this paper, we give an outline of the LinGO(More)
Multiword expressions are a key problem for the development of large-scale, linguistically sound natural language processing technology. This paper surveys the problem and some currently available analytic techniques. The various kinds of multiword expressions should be analyzed in distinct ways, including listing " words with spaces " , hierarchically(More)
We develop a framework for formalizing semantic construction within grammars expressed in typed feature structure logics, including HPSG. The approach provides an alternative to the lambda calculus; it maintains much of the desirable flexibility of unification-based approaches to composition, while constraining the allowable operations in order to capture(More)
We describe minimal recursion semantics (MRS), a framework for semantics within HPSG, which considerably simpliies transfer and generation. We discuss why, in general, a semantic representation with minimal structure is desirable for transfer and illustrate how a descriptively adequate representation with a non-recursive structure may be achieved. The paper(More)
Semantic representations provide an abstraction which allows generalisations to be made across very different surface forms and different syntactic formalisms. But deriving conventional semantic representations requires more information than can be extracted from morphology and syntax, even by deep grammars. The standard way of dealing with this is to use(More)