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EN
This article explores the distinction between paradigmatic semantic relations, both from a cognitive and a computational linguistic perspective. Focusing on an existing dataset of German synonyms, antonyms and hypernyms across the word classes of nouns, verbs and adjectives, we assess human ratings and a supervised classification model using window-based and pattern-based distributional vector spaces. Both perspectives suggest differences in relation distinction across word classes, but easy vs. difficult class-relation combinations differ, exhibiting stronger ties between ease and naturalness of class-dependent relations for humans than for computational models. In addition, we demonstrate that distributional information is indeed a difficult starting point for distinguishing between paradigmatic relations but that even a simple classification model is able to manage this task. The fact that the most salient vector spaces and their success vary across word classes and paradigmatic relations suggests that combining feature types for relation distinction is better than applying them in isolation.
2
EN
The main goal of the paper is to show the idea of incorporating paradigmatic and syntagmatic relations into processing data stored in information tables using rough set methods. Input data, in a tabular form, are used in many machine learning and computational intelligence methods and algorithms, among others, those based on rough set theory. Additional knowledge about semantic relations (both paradigmatic and syntagmatic) can be considered as a useful context affecting data classification or clustering.
EN
Intellectualization of the information retrieval process requires appliance of the specialized linguistic resources. The domain specific linguistic ontology might be one of such resources. This article presents software organization method for automated formation of the ontological knowledge base by converting structured encyclopaedic resource to the appropriate ontology objects. The concepts ontology database creation procedures, concepts hierarchies and associative relations networks are presented and also studies of the qualitative and quantitative composition of the current experimental ontology based on Ukrainian Wikipedia segment are performed.
PL
Intelektualizacja procesu wyszukiwania informacji wymaga urządzenia z wyspecjalizowanymi zasobami lingwistycznymi. Specyficzna ontologia językowa może być domeną jednego z takich zasobów. W artykule przedstawiono oprogramowanie do automatycznego tworzenia bazy wiedzy ontologicznej przez konwersję zorganizowanych zasobów encyklopedycznych do odpowiednich obiektów ontologicznych. Przedstawiono koncepcję procedury tworzenia bazy danych ontologii, koncepcję hierarchii oraz sieci relacji, a także przeprowadzone badania jakościowego i ilościowego składu bieżącej ontologii eksperymentalnej opartej na ukraińskiej wersji Wikipedii.
4
EN
This paper deals with certain morphosemantic relations between Croatian verbs and discusses their inclusion in Croatian WordNet. The morphosemantic relations in question are the semantic relations between unprefixed infinitives and their prefixed derivatives. We introduce the criteria for the division of aspectual pairs and further discuss verb prefixation which results in combinations of prefixes and base forms that can vary in terms of meaning from compositional to completely idiosyncratic. The focus is on the regularities in semantic modifications of base forms modified by one prefix. The aim of this procedure is to establish a set of morphosemantic relations based on regular or reoccuring meaning alternations.
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