Grammatical Framework (GF) is a special-purpose functional language for defining grammars. It uses a Logical Framework (LF) for a description of abstract syntax, and adds to this a notation for defining concrete syntax. GF grammars themselves are purely declarative, but can be used both for linearizing syntax trees and parsing strings. GF can describe both formal and natural languages. The key notion of this description is a grammatical object, which is not just a string, but a record that contains all information on inflection and inherent grammatical features such as number and gender in natural languages, or precedence in formal languages. Grammatical objects have a type system, which helps to eliminate run-time errors in language processing. In the same way as an LF, GF uses...

Abstract. The Grammatical Framework GF is a grammar formalism designed for multilingual grammars. A multilingual grammar has a shared representation, called abstract syntax, and a set of concrete syntaxes that map the abstract syntax to different languages. A GF grammar consists of modules, which can share code through inheritance, but which can also hide information to achieve division of labour between grammarians working on different modules. The goal is to make it possible for linguistically untrained programmers to write linguistically correct application grammars encoding the semantics of special domains. Such programmers can rely on resource grammars, written by linguists, which play the rôle of standard libraries. Application grammarians use resource grammars through abstract interfaces, and the type system of GF guarantees that grammaticality is preserved. The ongoing GF resource grammar project provides resource grammars for ten languages. In addition to their use as libraries, resource grammars serve as an experiment showing how much grammar code can be shared between different languages. 1.1. Multilingual grammars 1.

Morphological lexica are often implemented on top of morphological paradigms, corresponding to different ways of building the full inflection table of a word. Computationally precise lexica may use hundreds of paradigms, and it can be hard for a lexicographer to choose among them. To automate this task, this paper introduces the notion of a smart paradigm. It is a metaparadigm, which inspects the base form and tries to infer which low-level paradigm applies. If the result is uncertain, more forms are given for discrimination. The number of forms needed in average is a measure of predictability of an inflection system. The overall complexity of the system also has to take into account the code size of the paradigms definition itself. This paper evaluates the smart paradigms implemented in the open-source GF Resource Grammar Library. Predictability and complexity are estimated for four different languages: