Smart Paradigms for Lexicon Construction

Sammanfattning: Because lexica are such an important part of language technology, it is important to look for methods that can help us create and update those lexica. In this thesis, we present some work done around the notion of smart paradigm. Smart paradigms are created in the hope that they will decrease the amount of work of the lexicographer who wishes to create or update a morphological lexicon. In the first paper, we evaluate smart paradigms implemented in GF: how good are they to guess the correct inflection tables? How much information is required? How good are they at compressing the lexicon? In the second paper, we take some distance from the smart paradigms: although they have been used in this work, they are not the main focus of the study. Instead, we compare two rule-based machine translation systems based on different translation process and try to determine the potential of a possible hybridization. Finally, in the last paper we come back to the smart paradigms. If the smart paradigms can reduce the work of the lexicographer, someone still needs to create them in the first place. In this paper we explore the possibility of automatically creating smart paradigms based on existing, traditional paradigms using machine learning techniques.