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: English, French, Swedish, and Finnish. The main result is that predictability does not decrease when the complexity of morphology grows, which means that smart paradigms provide an efficient tool for the manual construction and/or automatically bootstrapping of lexica.
Furthermore, REF introduce an implementation of Smart Paradigms -heuristically organized paradigms minimizing the number of forms needed to predict the full paradigm of a particular lexeme.
Smart Paradigms and the Predictability and Complexity of Inflectional Morphology
EACL
Computer Science