We present a tool that facilitates the efficient extension of morphological lexica. The tool exploits information from a morphological lexicon, a morphological grammar and a text corpus to guide the acquisition process. In particular, it employs statistical models to analyze out-of-vocabulary words and predict lexical information. These models do not require any additional labeled data for training. Furthermore, they are based on generic features that are not specific to any particular language. This paper describes the general design of the tool and evaluates the accuracy of its machine learning components.
['Tobias Kaufmann', 'Beat Pfister']
Semi-automatic extension of morphological lexica