Modelling Processes of Ukrainian-Language Text Linguistic Analysis

1 IntroductionOrganizations focus on automate their processes in order to improve efficiency, reduce costs, and/or reduce human beings' errors in an easy and rapid manner. Business process management (BPM) methods provide a solution to this issue. In this context, information systems like CRM, ERP, SCM, etc. have known an increasing demand. The main problem consists of the length of the business process specifications. If new regulations appear, these specifications must be adapted. Manually extraction of visual models is time consuming. During time, a series of solutions were proposed. The literature shows a crowd of approaches that extracts data models [1], [2], [3], and process models [4], [5] from Natural Language (NL) text. This paper aims to analyze the Natural Language Processing (NLP) techniques and tools used in order to provide different types of visual representations.On the last few years, approaches based on NLP have been developed in order to automate process conversion from NL text. NLP plays an important role in NL text analysis as NLP tries to understand speech and text as humans beings would do. Colloquialism, abbreviations or typos make this task a challenging one. NLP has the origins in 1950s when Alan Turing proposed the Turing test [6], by introducing the imitation game. Since then, the literature shows a plethora of NLP tools [7], [8], [9], [10] using several machine learning techniques, our focus being on those applied on data models and process models discovery from NL text, starting with the first language parser [11] to the actual ones like NLTk [7], [8], ANTLR1, etc.Linguistic analysis is closely tied to NLP. Liddy [12] highlights 7 levels of linguistic analysis: a) Phonetic or Phonological level: how words are pronounced, b) Morphological level: prefixes, suffixes and roots analysis, c) Lexical level: word level analysis including lexical meaning and Part-Of-Speech (POS) analysis, d) Syntactic level: grammatical analysis of words in a sentence, e) Semantic level: determining the possible meanings of sentences, f) Discourse level: interpreting structure and meaning for texts larger than a sentence, g) Pragmatic level: understanding the purpose of a language.Some of the problems approached by NLP are: POS tagging, parsing, Named Entity Recognition (NER), chunking, Semantic Role Labeling (SRL). Anaphora resolution [13] refers to the interpretation of the link between the anaphor and its antecedents.The remainder of the paper is organized as follows: Section 2 briefly outlines the NLP domain, describing the levels of linguistic analysis and the main NLP approaches of analyzing NL requirements. Section 3 focuses on data and process models extraction from NL text. This section makes an introduction to Object Oriented Analysis and Business Process Modeling and analyses the existing tools that discover data and process models from text. Subsequently, Section 4 summarizes the results of this work and the conclusions are drawn in Section 5.2NLPA detailed review on NLP is given in [14] and in [15]. Jones [14] divides the history of NLP into four phases: the first starts at the beginning of the 1940s and lasts to the late 1960s, the second begins from the end of 60s and lasts to the end of 70s, the third is represented by late 80s, where the fourth phase starts in the late of 90s. Next, we will detail each phase as they were defined in [14] and [15]. First phase treated machine translation issues, while the second focused on artificial intelligence. The third phase can be called grammatico-logical phase, which is followed by the lexical phase. A fifth phase is proposed in [16] where formal theories and statistical data are combined. Since this study was published first in 1994 and then it was re-organized in 2001 we can add the sixth phase: from 2000 until present where NLP techniques are combined in order to contribute to visual models extraction.Software requirements are usually written in NL which is asymmetric and irregular [17]. …

This article represents approaches of the artificial intelligence methods, used in public administration. An overview of various technologies of artificial intelligence applications in the field of public administration and related fields is given. All of these research directions are particularly relevant to the task of digital technologies (including artificial intelligence) growth to create an efficient and competitive digital economics in Russia. Among the modern intellectual technologies that allow solving the widest range of tasks, an important role plays technologies related to natural language text processing - nonstructured NL-texts are essential segment of data, used for analysis and decision-making tasks (in terms of data volume, of course, video data have a leading position, however, they are usually suitable for solving tactical but not strategic management tasks). The article provides an overview of the existing methods of natural language processing and their practical application to the tasks of public administration. An integrated approach to the natural language processing tools using for solving practical problems in the field of public administration is considered on the example of the ISIDA-T system for extracting information from natural language texts, developed at the Artificial Intelligence Research Center PSI RAS. The system under consideration is distinguished by a modular approach to the pre-processing of unstructured text and the possibility of manual adjustment for a specific extraction task. This technological solution gives the necessary flexibility and ease of use. The system consists of configurable text preprocessing, linguistic analysis, target information retrieval and output of the results in user-friendly form modules. One of the important components of the system is an integrated knowledge resource that allows quickly and efficiently adjust the system to the specifics of the relevant subject area. An approach to the application of the ISIDA-T system to the task of fact information extraction (as the most important for analyzing the situation and subsequent management decisions) is proposed using the example of information extraction about resignations and appointments from news feeds.

The paper aims at bringing up a type of text linguistic analysis, different from traditional one, with the emphasis on the contrastive studies in general and on the English-Albanian cross-linguistic phenomena in particular. It will concentrate in explaining some of the most intriguing and most diverse text analysis elements having in mind the following text categories: Point of view, Composition, Text Idioms. A grammatical structure (Relative Constructions) has been examined thoroughly within the translation method analysis, out of and within the co-text analysis. It resulted in two different outcomes: traditional direct method analysis on one side and text linguistic co-text analysis on the other. Text linguistics as a special field of studies has been greatly developed due to the increased number of translations from one language into another. Text analysis, which relies on the deep description of micro and macro text elements of the text, is crucial for determining the level of translation accuracy of a particular text. Having in mind the relevance of recent discourse and pragmatic analyses impact in the development of interdisciplinary studies, the explanation of constituent elements of the written text is of great importance for the contrastive text studies or translation studies respectively.

This research aims to contribute to the answers to the following two questions: how did the infodemic develop in the digital information media, and what was the relationship between the infodemic and the development of the pandemic? We suggest that the first step towards a better understanding of the COVID-19 infodemic is to perform a quantitative analysis of news articles published on online portals. The main goal of this study is to provide an overview of the trends of COVID-19 related articles published on online news portals during the first six months of the pandemic in Croatia. We propose a three-step analysis of texts: (i) analysis of the number of articles related to COVID-19, (ii) investigation of the correlations between the number of articles and the number of daily COVID-19 cases and (iii) linguistic analysis of texts (observing the most frequent keywords and how the trends change during the time). Based on the results of investigating the correlation between the number of published news-articles and the number of daily reported cases of infection shows that the news portals insist on the pandemic as a topic even when the events that generate it are no longer at their peak.

This paper presents a computer-based frequency distribution analysis to decode the pragma-stylistic meanings in one of the narrative discourse represented by Orwell’s dystopian novel Animal Farm. The main objective of the paper is to explore the extent to which computer software contribute to the linguistic analysis of texts. The paper uses the variable of frequency distribution analysis (FDA) generated by concordance software to decode the pragmatic and stylistic significance beyond the mere linguistic expressions employed by the writer in the selected data. Some words were selected to undergo a frequency distribution analysis so as to highlight their pragmatic and linguistic weight which, in turn, helps arrive at a comprehensive understanding of the thematic message intended by the writer. The paper is grounded on one analytical strand: Frequency distribution analysis conducted by concordance. Results reveal that applying a frequency distribution analysis to the linguistic analysis of large data fictional texts serves to (i) identify the various types of discourse in these texts; (ii) create a thematic categorization that is based on the frequency distribution analysis of specific words in texts; and (iii) indicate that not only high frequency words are indicative in the production of particular pragmatic and stylistic meanings in discourse, but also low frequency words are highly indicative in this regard. These results accentuate a further general finding that computer software contribute significantly to the linguistic analysis of texts, particularly those pertaining to literature. The paper recommends further and intensive incorporation of computer and CALL (computer-assisted language learning) software in teaching and learning literary texts in EFL (English as a foreign language) settings.

Ohmann’s (1964) transformational manipulations support the School of Linguistic Stylistics that sees style as choice and asserts that choice, a tool in Linguistic Stylistics, is related to performance rather than competence. Consequently, this study explores Transformational Generative Grammar (TGG) Approach to Linguistic Stylistic Analysis of texts as it focuses on Ohmann’s identified transformational manipulations; reordering, combination, addition and deletion in “Black laughter”, culled from Raji-Oyelade’s (1997) collection of poems, a Harvest of Laughters, purposively selected as the text for the analysis. The paper identifies the extent to which this text upholds the assertion that style is choice and the extent to which the argument that choice is related to performance rather than competence can be generalized. The study shows that the selected text contains and uses the transformational manipulations that enhance deeper understanding, interpretation and analysis of the selected text, and that it is generalizable that performance is the basis for style as choice since performance is the dexterity that showcases competence. In conclusion, it corroborates Ohmann’s claim that TGG is potentially useful in linguistic stylistic analysis of texts.

The last decade has seen an explosion of readily available digital text that has rendered attempts to analyse and classify by hand infeasible. As a result automatic processing of natural language text documents has become a main research interest of Artificial Intelligence (AI) and computer science in general. It is probably fair to say that after multivariate data, natural language text is the most important data format for applications. Its particular characteristics therefore deserve specific attention. We will see how well-known techniques from Information Retrieval (IR), such as the rich class of vector space models, can be naturally reinterpreted as kernel methods. This new perspective enriches our understanding of the approach, as well as leading naturally to further extensions and improvements. The approach that this perspective suggests is based on detecting and exploiting statistical patterns of words in the documents. An important property of the vector space representation is that the primal–dual dialectic we have developed through this book has an interesting counterpart in the interplay between term-based and document-based representations. The goal of this chapter is to introduce the Vector Space family of kernel methods highlighting their construction and the primal–dual dichotomy that they illustrate. Other kernel constructions can be applied to text, for example using probabilistic generative models and string matching, but since these kernels are not specific to natural language text, they will be discussed separately in Chapters 11 and 12.

The article presents new results of the research on the problem of communicative formation of the image of environmentally disadvantaged territories. The relevance of the issue is supplemented by new factors in the context of environmental discourse and language images of the territory in the regional media. The ecological image of the territory acquires relevance in the concept of sustainable development. The aim of the study is to try to identify the features of environmental news coverage in the regional media of environmentally disadvantaged territories, linguistic patterns of image creation in the news content. The key toolkit was the method of content analysis and survey, contributing to the understanding of the problem. The methodology and methods of research are built on the scientific approaches of domestic and foreign scientists, who raise the problem at the methodological level. A special place in the methodology of analysis is taken by the linguistic analysis of texts. The angle of presentation and consideration of the problem is important. Informational environmental agenda of Internet media of industrial regions becomes a conditional mirror, which reflects the current reality. The results of the study showed that there is a direct link between the image of the territory and its information promotion in the information agenda of the region, which forms the communicative image of the territory in the media space. The assumption that language images influence the attractiveness of the region is confirmed. The scientific novelty of the research consists in the attempt to integrate the methods of classical content analysis of the environmental agenda of the regional media and methods of linguistic analysis in environmental communications. The practical significance of the study lies in the possibility to use the materials to translate the experience of the regional media in the practice of environmental journalism, forming the impression and representation of the attractiveness of the risk territories.

An universal method for wordform recognition and generation is proposed. It includes the model of word formation in natural languages and algorithms for wordform generation and recognition. In the wordformation model, abstracting from typical notions in the morphology of natural languages takes place Actual problems of machine translation, spelling checking, text analysis and knowledge extraction from them, computer–user dialog in a natural language, analysis of queries in information search systems of global information networks include multilevel automatic text processing. This levels are morphological, syntax and semantic. There are a large number of methods for solving the morphological level problems in text processing (see short review in [1]). However, they are designed for one or several languages that are similar in their word formation. At the same time, in connection with worldwide globalization, it is topical to develop applications for text pro cessing in different languages. Therefore, the necessity arises to create a method for morphological processing of texts in natural languages of different groups and families. This work proposes a universal method for the generation and recognition of word forms independent of the formation type and capable of processing the entire paradigm of a word. The method includes a model for the formation and wordform generation and recognition algorithm. The Model of formation in a natural language (below the model of formation) implies that the generation of any word form with a given grammatical meaning can be presented as the sequence of a finite number of transformations of the base. The method of presenting formation, as well the generation and recognition algorithms are interrlated. On the one hand, one part governs the other. On the other, simplification of one part causes complication of the other. The objective of the word form generation algorithm is to obtainthe word form F corresponding to the base S and grammatical meaning G. The result of word form generation is always unambiguous. The input data are S and G. The output data are F. The generation algorithm consists of two stages. At the first stage a required transformation chain R is searched using the input data, the base S, and grammatical meaning G. The second stage is the application of the found chain R to the base S to obtain the required form F. The wordform recognition algorithm recognizes the grammatical meaning G and the base S that correspond to the starting word form F. The input data are F. The output data are S and G. This algorithm consists in searching the chains of transformations in a cycle. At each iteration, a new chain Ri is taken as well as a respective base type Ti and a grammatical meaning Gi. Further, the next reverse chain is applied to the starting word form F to obtain the base Si. If the same base type Ti corresponds to the found base Si and the next chain then the result that consists of the obtained chain Si and the grammatical meaning Giis added to the obtained results. Thus, the iteration is completed and a transition to the next iteration occurs. The number of iterations equals n, the number of the chains of transformations. Thus, we have developed a universal method for wordform generation and recognition that includes the model of formation and the processing algorithm. The proposed processing algorithms are applicable to natural languages of different groups and families. Algorithms for the Russian, German, Spanish, and Finnish languages were successfully tested. The transformation chains were classified and the algorithm of automated construction of transformation chains was proposed based on this classification.

The work analyzes the concept of “Mental activity” as a component of the linguistic personality of a child during his infancy and early childhood on the linguistic material of the first book of the autobiographical novel by I.A. Bunin’s “Life of Arseniev”. Thus, the subject of the research is the linguo-cognitive model of the concept of “Mental activity” with a core and a system of peripheral means. Cognitive activity as a component of the characteristics of a linguistic personality occupies an important place in cognitive linguistics. Thus, the relevance of the presented article lies in the appeal to the phenomenon of the linguistic personality of the character of a work of art, the problem of its typology and method of description. The purpose of the article is to identify and then analyze the lexical means of representing the concept of “Mental activity” and its func-tioning in the novel based on statistical, descriptive methods and the method of conceptual analy-sis. In the conclusions reached by the author of the article, it is substantiated that the mental activity of a child reflects the specifics of his age and intellectual development, the characteristics of his environment, the socio-economic and cultural-historical conditions in which he grows up, is associated with the communicative strategies of his linguistic personality. The materials of the article can find practical application in university courses on textual criticism, cognitive linguistics, and linguistic text analysis.

The article concentrates on the key-aspects vital in analysis of poetic text in the process of Russian Language teaching for foreigners. Linguistic and stylistic analysis of poetic text helps to determine its hidden semantics. Linguistic and stylistic interpretation encompasses detailed analysis of all language characteristics in their interaction.

В статье рассмотрены сложные механизмы кодового переключения. Основной научной проблемой является выявление структурных, прагматических и социолингвистических аспектов кодового переключения, которые влияют на понимание идентичности и социального взаимодействия. Исследовательский вопрос заключается в том, как кодовое переключение отражает культурно-специфические и социальные значения, взаимодействуя с контекстом. Цель исследования – определить прагматические и метапрагматические функции кодового переключения. Материалом исследования послужил дебютный роман Розанны Амаки «Книга Эха», который был подвергнут детальному лингвистическому и социолингвистическому анализу. Основной метод – лингвистический анализ текста, включающий лингвостилистический, лексико-семантический и контекстуальный подходы. Основные результаты исследования показывают, что кодовое переключение выполняет различные функции, включая выражение социальных статусов, культурной идентичности и эмоциональных состояний персонажей. Новизна исследования заключается в интеграции этнопсихологического подхода к общему анализу. The article examines the complex mechanisms of code-switching. The main research problem is identifying the structural, pragmatic, and sociolinguistic aspects of code-switching that affect the understanding of identity and social interaction. The research question focuses on how code-switching reflects culturally specific and social meanings in interaction with context. The purpose of the study is to determine the pragmatic and metapragmatic functions of code-switching. The research material is Rosanna Amaka's debut novel “The Book of Echoes”, which underwent detailed linguistic and sociolinguistic analysis. The primary method used is linguistic text analysis, incorporating linguo-stylistic, lexico-semantic, and contextual approaches. The main findings of the study reveal that code-switching performs various functions, including expressing social statuses, cultural identity, and emotional states of characters. The novelty of the research lies in integrating an ethnopsychological approach into the overall analysis.

The article provides an analysis of perceptual images in the aspect of text-related activities based on the poems by the Slovak symbolist poet Ivan Krasko. The focus is placed on the linguistic means of expressing perceptual semantics which allow exploring the artistic picture of the author’s world within the given literary direction. The problem of artistic perception is examined in the context of current research in the field of lin-guistic semantics and philological analysis of literary texts. In the first part of the article, the authors give a definition of a perceptual image, understood as one of the forms of an artistic image that is filled with a specific lexical and semantic content in the author’s individual worldview. A review of the works of Slovak researchers who discuss the features of the symbolist poetry of Ivan Krasko is given. It is emphasized that the creativity of the Slovak symbolist is characterized by poetic parallelism between the internal state of the lyrical hero and their surrounding nature. Sensory perception in the poetry of Ivan Krasko is focused on the awareness and classification of “perceived” objects and phenomena. The second (main) part of the article deals with a comparative linguistic analysis of the original poem “My Songs” and its poetic translation by Anna Akhmatova. The most significant artistic image in the original and translated text is všednosť/ordinariness (everydayness), which reflects the internal state of the lyrical hero and is represented by a wide range of linguistic units with perceptual semantics. The analyzed perceptual images are fog, haze, poplar, mountains, flowers, etc. At the lexical level, there are similar features in the description of the landscape: nouns and adjectives with semantics of visual perception are used – greenness, whiteness, blue-ness. The differences at the formal-syntactic level are due to the peculiarities of the syntactic structure of the Slovak language and the Russian language, while the proposi-tional semantics generally corresponds. At the stylistic level, minor differences are explained by the author’s worldview: in case of Krasko, it is a symbolist worldview; in case of Akhmatova, it is the acmeist worldview. In the original text, the main images are represented by expressions with an abstract meaning: božie muky dole v cintoríne, striebro riavy, v dolinu, vzkvetlú tisícerým kvetom; in translation, the images are more specific: crucifixion, a rose hip, a crest, a cliff. As a result of the comparative analysis of the original and translated texts, the peculiarities of the representation of the percep-tual picture of the world of the author and the translator, realized at different text levels, were revealed. Poetic transformations testify to the “special type of perception” charac-teristic of the Slovak poet as a representative of the symbolist trend.

This research examines the narrativization of Ukrainian identity in Timothy Snyder's historical work "The Reconstruction of Nations: Poland, Ukraine, Lithuania, Belarus, 1569-1999" through the lens of postcolonial criticism and cognitive linguistic analysis.The study addresses the complex positioning of Central and Eastern Europe as an intermediate region with a contradictory identity, particularly focusing on Ukraine's agency and subjectivity within broader European imperial contexts.The research employs frame analysis using S. Zhabotynska's cognitive domains (subject, actional, possessive, identification, and comparative) to analyse how Ukrainian identity is constructed and represented in Snyder's narrative.The methodology incorporates corpus linguistic analysis using BootCat, TagAnt, and AntConc programs to identify linguistic markers and collocational patterns associated with Ukrainian identity discourse.The theoretical framework draws upon postcolonial theory, particularly Edward Said's concept of colonial discourse persistence beyond imperial dissolution, and applies it to the postcommunist context of Central and Eastern Europe.The study distinguishes between two scholarly approaches to postcommunist societies: ontological claims to postcoloniality, emphasising historical lack of subjectivity, and analysis of colonial forces' balance across different historical moments.Results demonstrate that T. Snyder's work presents Ukraine as a modern nation with distinct agency, challenging colonial narratives that position Ukraine as merely peripheral to metropolitan centres.The frame analysis reveals predominant use of subject and actional domains, with Ukraine conceptualised as an active entity capable of independent action rather than the passive object of imperial manipulation.Corpus analysis identifies key collocations emphasising political agency (activists, state, independence, nationalism) and social stratification (peasants, gentry, elites, patriots).The research reveals T.Snyder's deployment of conceptual metaphors, personification, evaluative vocabulary, and action verbs to construct the Ukrainian identity narrative.These linguistic strategies serve to establish Ukrainian historical subjectivity and counter persistent colonial frames that marginalise Ukrainian agency.The study concludes that frame analysis using cognitive domains effectively reveals Ukrainian identity narrativization patterns in historical discourse.The postcolonial critical perspective successfully demonstrates Ukraine's agency within Central and Eastern European historical contexts, challenging destructive propaganda narratives through rigorous linguistic and conceptual analysis of scholarly historical texts.

The article discusses promising directions for the use of modern automatic methods for analyzing natural language data for solving a wide range of practical problems. The technology of creating electronic corpora (collections) of texts is considered as a tool for the transition from model linguistics to tagged data linguistics. The principles of the creation of marked corpora of texts, the possibilities and limitations of their use are considered. Creation of a marked corpus of texts in which language data that is downloaded from the Internet is processed sequentially before issuing the results to users is described. The conveyor consists of the following steps: uploading data from the Internet; definition of the language in which the text is written; unloading metadata; splitting the texts into paragraphs and sentences; deduplication; tokenization; automatic language markup; uploading cleared and marked data to the network. The prospects for the development of language data analysis systems are presented. Requirements for the creation of corpora for solving problems of public administration and strategic planning are developed. Properties that should have such bodies are considered. Those include: corpus format, corpus volume, the degree of the linguistic analysis depth, corpus-manager structure. A description of the marked corpora of texts developed at the Artificial Intelligence Research Center (AIReC) of Ailamazyan Program Systems Institute of the Russian Academy of Sciences, with a reference to the tasks of extracting information about persons, events and situations from the texts of news reports is presented. A retrospective review of the development of systems for automatic processing of natural language texts in the areas of machine translation and human-machine interaction is given.