Assigning an Inflectional Paradigm using the Longest Matching Affix

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A probabilistic model for guessing base forms of new words by analogy

Volume: 4919 Host publication title: Computational Linguistics and Intelligent Text Processing 9th International Conference, CICLing 2008, Haifa, Israel, February 17-23, 2008. ProceedingsPeer reviewe

Guessers for Finite-State Transducer Lexicons

Language software applications encounter new words, e.g., acronyms, technical terminology, names or compounds of such words. In order to add new words to a lexicon, we need to indicate their inflectional paradigm. We present a new generally applicable method for creating an entry generator, i.e. a paradigm guesser, for finite-state transducer lexicons. As a guesser tends to produce numerous suggestions, it is important that the correct suggestions be among the first few candidates. We prove some formal properties of the method and evaluate it on Finnish, English and Swedish full-scale transducer lexicons. We use the open-source Helsinki Finite-State Technology to create finitestate transducer lexicons from existing lexical resources and automatically derive guessers for unknown words. The method has a recall of 82-87 % and a precision of 71-76 % for the three test languages. The model needs no external corpus and can therefore serve as a baseline.Peer reviewe

Corpus-based paradigm Selection for morphological entries

Volume: 4 Host publication title: Nealt Proceedings Series Vol. 4 Host publication sub-title: Proceedings of the 17th Nordic Conference of Computational Linguistics NODALIDA 2009Peer reviewe

Entry Generation for New Words by Analogy for Morphological Lexicons

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