A Bare-bones Constraint Grammar

Abstract. This paper presents a solution for overcoming the lexical resource gap when mounting rule-based Constraint Grammar systems for minor languages, or in the face of licensing and financing limitations. We investigate how the performance of a CG disambiguation grammar responds to shifting input parameters, among them lexicon limitations of various degrees, the lack a morphological analyzer or both. We propose solutions for a bare-bones system, introducing endings heuristics and so-called morphological APPEND rules. For English, even with an unadapted disambiguation grammar, our bare-bones tagger achieved F-scores of 90-96 % for part of speech, and 94-97 % for lemmatization, depending on the modules and mini-lexica used