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EN
The use of information technology in linguistic research gave rise in the 1950s to what is known as Natural Language Processing, but that framework was created without paying due attention to the need for logical reconstruction of linguistic concepts which were borrowed directly from barely (or even not at all) formalised structural linguistics. The Computer-aided Acquisition of Semantic Knowledge project (CASK) based on the Knowledge Discovery in Databases technology (KDD) enabled us to interact with computers while gathering and improving our knowledge about languages. Thus, with the help of data mining tools, as a result of revisiting two sorts of generally admitted linguistic theories (the Predicate Argument Structure theory and Information Structure theory), we succeeded in improving these local linguistic approaches by proposing to unify the Associative Semantics (AS) theory (in which we introduced the concept of ortho-information) with the Meta-Informative Centering (MIC) theory (in which we described the meta-informative layer of natural languages). The resulting Distributed Grammar (DG) program (sketched out in this paper) treats, in addition to the above types of information, the third one, para-information (concerning identity and alikeness with respect to context and language ontology) which – despite many studies – had no uniform theoretical background in general linguistics. This DG program aims to lay the foundations for creating the theoretical background of Conceptual Linguistics.  
EN
The article deals with computer science models (CSMd), that is, formal constructions which are described theoretically in the language of computer science (the language of algorithms and data structures), and which can therefore, be implemented in the form of applications and activated on a computer. After distinguishing different kinds of CSMd (e.g. theoretical and real) and presenting some examples of CSMd (especially in the field of mental phenomena) we discuss in detail the modeling procedure. This procedure can be initiated by a metaphor (understood as an initial, informal image of a studied phenomenon), has a cyclical and open character, and – according to our methodological reconstruction – consists of four stages: abstraction, formalization, simplification and verification. We discuss these stages in the context of computer science, referring to four elements: the studied domain, a meta-theory (always formal), the constructed theory of the studied domain (formalized in the language of meta-theory), and the constructed model (always temporary). We present a simplified scheme of the whole procedure and identify three cycles of the modeling loop: small, proper and wide. Finally we claim that contemporary CSMd (especially computer science models of the mind) should be constructed using artificial intelligence tools, such as machine learning and data mining techniques.
EN
The idea of the three-tier information structure in the content of utterances is the result of research carried out in a transdisciplinary spirit, within sciences such as linguistics, psychology, logic and computer science. The theory of Meta-Informative Centering (MIC) of attention, which borrows the concept of attention centering from psychology and the concept of information from computer science, makes it possible to treat ―information structures" or "thematic-rhematic structures" as strictly dependent on the canonical form of utterances (as the manifestation of predication). Thus, an important feature of the MIC theory is its reference to predication, and in particular to the language of classical logic (first-order predicate logic). In the light of MIC theory, "information structure" appears in fact to be a structure of meta-information (representing "information about information") with respect to orthoinformation (proper information; i.e. situation frame, its types and aspects, roles, spatio-temporal anchors etc.) contained in the utterances. It is the theory of Associative Semantics (AS), which is being developed in parallel to the theory of MIC, which constitutes the layer of ortho-information. However, the foundational role in the structure of information content of utterances is played by para-information ("information which is similar or related to some other information"). In order to treat systematically the structure of information (ortho-, meta- and para-information) as contained in language utterances, and for representing their fundamental components, we proposed using ―formal concepts‖ belonging to the rapidly developing new field of research in computer science under the general name of ―Formal Concept Analysis‖ (FCA). The most important operations (responsible for the structure of information contained in the body of the utterances) are as follows: (a) selection (for building conceptual areas of interest in the para-information tier), (b) configuration (for building relationships between concepts in the ortho-information tier) and (c) centering (secondary selection of concepts for transmitting in the meta-information tier), while the most important operations (responsible for the structure of utterances) are: (a) nesting (for building utterances as units of discourse in the profile, across the tiers) and (b) encapsulation (for designating the conceptual space and combining conceptual representations with the language). In this paper we present one of the many areas of application of the described theoretical foundation, namely: word order in linguistic typology. Research taking into account the abovementioned three kinds of information constitutes a contribution to the construction of a coherent theoretical framework for Distributed Grammar (i.e. multi-tier grammar with a generalized idiomatics).
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