Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/40609
Type of publication: research article
Type of publication (PDB): Straipsnis kitose duomenų bazėse / Article in other databases (S4)
Field of Science: Filologija / Philology (H004)
Author(s): Rimkutė, Erika;Grigonytė, Gintarė
Title: Automatizuotas lietuvių kalbos morfologinio daugiareikšmiškumo ribojimas
Other Title: Automated Disambiguation Of Lithuanian Morphological Ambiguity
Is part of: Kalbų studijos = Studies about languages. Kaunas : Technologija, 2006, nr. 9
Extent: p. 30-37
Date: 2006
Keywords: Kompiuterinė lingvistika;Morfologinis daugiareikšmiškumas;Computational linguistic;Language;Morphological ambiguity;Statistical and logical methods
Abstract: We describe methods for disambiguation of Lithuanian morphological ambiguity. The methods we present can be automatic and automated. Automatic are statistical and logical methods, also the removal of unreal homonyms. Automated methods are: the removal of unreal homoforms, disambiguation of non-inflective and inflective parts of speech. We need various rules for disambiguation of non-inflective parts of speech. Analysis of punctuation, statistical date from Contemporary Lithuanian Language Corpus, syntactic analysis, semantics, exhaustive analysis of all the text or a few nearest sentences, transformation in more clear words, morphological information, etc. can be useful for this disambiguation. The best method for disambiguation of inflective parts of speech is an automatic syntactic analysis. Syntactic rules we present are based on Dependency Grammar. These rules consist of two levels: the level of word groups (lower level) and the level of the combinations of word groups (upper level). It is very important to recognize which word is the main, i.e. governing, and dependent word in automatic syntactic analysis. Other relation parameters are: word order, insertion and priority (in some cases). We also have described the methodology of syntactic rules extraction in this article. Statistical and logical methods for disambiguation of morphological ambiguity gives good results – more than 90% of forms can be disambiguated correctly. At the meantime we have no concrete results what is an accuracy of automated disambiguation but it is clear that the automatic syntactic analysis can resolve many cases of morphological ambiguity of inflective parts of speech
Internet: https://hdl.handle.net/20.500.12259/40609
Affiliation(s): Kompiuterinės lingvistikos centras
Lituanistikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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