Ukrainian Texts Research Articles

Kárpátalja egyházi fenntartású iskoláinak virtuális nyelvi tájképe

We live in an age where everywhere we look, thousands of pieces of information are streaming towards us. This fact in itself highlights the importance of the linguistic landscape in our everyday lives, as everything that surrounds us, everything we perceive influences our thinking and therefore our use of language. In the 21st century, we need to pay particular attention to the virtual world, as a large percentage of the younger and even older generations receive a significant proportion of their stimuli through some types of electronic communication tools or social platforms. Schools have a particularly important role in language development and formation, as young people, the future generation, are most shaped within their walls. In the present study, we analysed a sample of posts published in the last few years on the social platforms (official website and Facebook) of the ecclesiastical schools of Transcarpathia. We relied on statistical and comparative analysis of the textual content of these entries. In addition, we examined the meta-linguistic information of the entries. The overall visual appearance of the website was also taken into consideration, i.e., the types of images published were also investigated. In the research, it was assumed that all the official webpages of the schools under investigation contain entries in both Ukrainian and Hungarian. We also assessed whether a higher percentage of entries in Hungarian appeared on the schools’ online interfaces. Results showed that the number of interactions by people who followed the sites was higher for Hungarian language posts, advertisements and articles. We assumed that religious posts and symbols regularly appeared on the websites and Facebook pages, and that a higher percentage of these posts and symbols appeared in Hungarian. It was also hypothesized that the volume of texts in Ukrainian was smaller than the amount of texts in Hungarian. The research has confirmed that both Ukrainian and Hungarian entries are found on the websites, with a higher share of entries in Hungarian. It also confirmed our hypothesis that followers of the websites tend to respond more frequently to posts in Hungarian, due to the fact that the majority of followers use Hungarian as their mother tongue. Last but not least, the research revealed that religious posts and symbols regularly appear on the official websites and Facebook pages of the lyceums, and the language of these posts is mostly Hungarian.

Optimizing hierarchical classifiers with parameter tuning and confidence scoring

Hierarchical classifiers play a crucial role in addressing complex classification tasks by breaking them down into smaller, more manageable sub-tasks. This paper continues a series of works, focused on the technical Ukrainian texts hierarchical classification, specifically the classification of repair works and spare parts used in automobile maintenance and servicing. We tackle the challenges posed by multilingual data inputs – specifically Ukrainian, Russian, and their hybrid – and the lack of standard data cleaning models for the Ukrainian language. We developed a novel classification algorithm, which employs TF-IDF victimization with unigrams and bigrams, keyword selection, and cosine similarity for classification. This paper describes a method for training and evaluating a hierarchical classification model using parameter tuning for each node in a tree structure. The training process involves initializing weights for tokens in the class tree nodes and input strings, followed by iterative parameter tuning to optimize classification accuracy. Initial weights are assigned based on predefined rules, and the iterative process adjusts these weights to achieve optimal performance. The paper also addresses the challenge of interpreting multiple confidence scores from the classification process, proposing a machine learning approach using Scikit-learn's GradientBoostingClassifier to calculate a unified confidence score. This score helps assess the classification reliability, particularly for unlabeled data, by transforming input values, generating polynomial parameters, and using logarithmic transformations and scaling. The classifier is fine-tuned using hyper parameter optimization techniques, and the final model provides a robust confidence score for classification tasks, enabling the verification and classification results optimization across large datasets. Our experimental results demonstrate significant improvements in classification performance. Overall classification accuracy nearly doubled after training, reaching 92.38 %. This research not only advances the theoretical framework of hierarchical classifiers but also provides practical solutions for processing large-scale, unlabeled datasets in the automotive industry. The developed methodology can enhance various applications, including automated customer support systems, predictive maintenance, and decision-making processes for stakeholders like insurance companies and service centers. Future work will extend this approach to more complex tasks, such as extracting and classifying information from extensive text sources like telephone call transcriptions.

DESCRIPTIVE TERMINOLOGY IN UKRAINIAN EPIGRAPHY: A CORPUS-BASED STUDY OF SYNONYMOUS TRIPLET “ГРАФІТІ”, “НАПИС”, AND “ЗАПИС”

The main goal of our study is to analyse the descriptive terminology used in academic discourse dedicated to Ukrainian epigraphy employing a corpus-based approach. Using the BootCat tool and custom tuples such as “епіграфіка графіті напис” and “корпус Україна графіті” we scraped the Web and generated a sample corpus containing Ukrainian texts related to Epigraphy. Our goal was to analyse the variety of epigraphic terms circulating the digital domain and the peculiarities of their usage. Our findings reveal variations in term usage in Ukrainian epigraphic texts, offering insights into their academic application. The case study showcased how synonyms can not only enrich a language, but also impose challenges in standardising terminology due to linguistic variations and the influence of individual scholars. The findings emphasise the need for a nuanced approach to developing standardised vocabularies, considering the linguistic, historical and cultural contexts. This study serves as a valuable example of how digital tools can aid in understanding and addressing the complexities inherent in preserving and studying cultural heritage in the digital age.

Using of NLP Methods in Intelligent Educational Systems

For the effective organisation of educational processes supported by relevant intelligent learning systems, it is important to choose the right technologies that would ensure individualisation of learning, adequate perception of learning content, and the so-called “understanding” of texts in Ukrainian provided by students (description of the solution to a task, answers provided in their own words, not selected from the test answer options, questions to the system, etc.), prototyping, constant iteration during natural language text recognition and processing, and maximum reliability and efficiency of learning processes. The purpose of the article is to study and analyse various methods of natural language processing, and the concept of NLP, and to consider common problems and prospects for developing a software product for processing Ukrainian-language text in online courses that support intelligent learning systems based on it. The research methods are the main methodological approaches and technological tools for analysing natural language texts in intelligent educational systems and developing a system for supporting NLP (Natural Language Processing) technology in the linguistic analysis of texts in Ukrainian. Such methods include, in particular: systemic and comparative analyses to identify the features of intelligence and information (with elements of intellectualisation) systems; the method of expert evaluation, which involves the study of literary sources and information resources, interviews and surveys of experts, as well as the processes of developing and testing intelligent and information systems. The novelty of the study is the analysis of modern technologies for the development of online educational process support systems through the organisation of processes of perception of information provided by students in natural language, the results of which can be used in the development of their software product to support the educational process in Ukrainian, ensuring the improvement of learning efficiency through the use of NLP technology in the process of studying the relevant academic content. Conclusions. The paper analyses modern NLP methods. The analysis has led to the selection of tokenisation, normalisation, stemming and lemmatisation methods for use in intelligent learning systems in the linguistic analysis of the so-called “free” communication in the natural (Ukrainian) language of students in the process of studying the educational content of online courses. During the tokenisation of Ukrainian-language texts, we solved such problems as eliminating so-called “merged” tokens, correcting spelling mistakes, identifying common prefixes in compound words and their impact on the semantics of the corresponding lexemes, identifying common prefixes in abbreviations, and bringing words to their normal form. Lemmatisation is especially important for the Ukrainian language (with its large number of cases of nouns, adjectives, word forms, etc.) and it requires the use of specially compiled dictionaries of the subject area under consideration. In these dictionaries, word forms are presented in the forms of lemmas (i.e., nouns are presented in the nominative case).

TRANSLATION STRATEGIES IN ENGLISH-UKRAINIAN RENDERING OF DUAL-NUMBER QUANTIFI

The article deals with translation strategies implemented in English-Ukrainian rendering of dualnumber quantifiers ‘both,’ ‘either,’ ‘neither’ that occur in modern fantasy fiction. The study aims to identify local and global translation strategies and methods of their adequate rendering at the post-translation stage of generalizing the translator’s experience. The research objectives are: 1) to compile a complete register of the lexemes under investigation based on J.K. Rowling’s “Harry Potter and the Prisoner of Azkaban” and its authorized Ukrainian translation produced by V. Morozov.; 2) to determine their semantic and functional characteristics and direct translation equivalents; 3) to identify their semantic roles and syntactic functions in the source text; 4) to specify the types of grammatical shifts and methods of their rendering into Ukrainian; 5) to identify and analyze the translation strategies applied by the translator to reach equivalence and adequacy of translation. The research material comprises 96 dual-number quantifiers used in the original text and their translations in the corresponding Ukrainian text fragments. In the course of the study, the following methods were employed: 1) entire sampling to compile a register of the lexemes and accomplish the source and target text levelling; 2) dictionary entries’ analysis to establish the lexical-semantic and functional properties of the quantifiers and their direct Ukrainian translation equivalents; 3) contextual analysis and immediate constituents’ analysis to identify their semantic roles and syntactic functions in the source text; 4) comparative-contrastive translation transformational analysis to specify the translation methods and types of grammatical shifts applied in their rendering; 5) to identify and analyze the translation strategies implemented by the translator; 6) quantity calculations to determine the frequencies of the analyzed phenomena. As a result, based on dictionary entries’ analysis, the main functional-semantic classes of the quantifiers have been found to be the determiner, pronoun, conjunction and pronominal adverb. By means of immediate constituents’ and contextual analysis, 17 pure and blended semantic roles of the lexemes’ referents in ‘state of affairs’ situations have been identified, the most frequent being the agent (36.4%), locative (14.6%) and experiencer (11.4%). By way of sentence parsing, 19 combinations of the semantic roles and syntactic functions have been established, the most frequent one being the agent subject (37.5%), the others showing frequencies around 10%. With the aid of translation transformational analysis, the most common methods of rendering the dual-number quantifiers into Ukrainian have been found to be omission (62.5%), equivalent (literal) translation (21.9%) and lexical substitution (15.6%). Correspondingly, the main translation strategies, including ST-oriented and TToriented ones, have been proved to be 1) communicative translation (68.8%) by omission with emphasis decrease, related and unrelated-word paraphrase, clause/sentence structure change and explicitness decrease, and by equivalent with emphasis change and clause/sentence structure change and/or addition; 2) literal translation (15.6%) including direct translation (4.2%) by pure equivalent and oblique translation (11.4%) by blended equivalent. i.e. with emphasis change and/or clause/sentence change; 3) semantic translation (15.6%) involving synonymy, emphasis change, phrase structure change, modulation, clause/ sentence structure change and explicitness decrease, 4) domestication (100%) incorporated in the above three strategies, all applied to ensure equivalence and adequacy of the translation.

Current Trends in the Use of Machine Learning for Error Correction in Ukrainian Texts

The article's authors have provided a detailed problem description of identifying and correcting errors in Ukrainian-language texts. This paper provides a detailed analysis of the latest research and publications aimed at solving the problems of identifying and correcting errors in Ukrainian-language texts. The analysis of modern tools related to error correction in texts is presented along with a comparative description. Investigated the existing data corpora for the Ukrainian language so that they are relevant to solving GEC tasks. Discovered the need to create a large annotated data corpus, which will be prepared by a special team with linguistic expertise. Analysed the opportunities, advantages and disadvantages of modern machine learning models that interpret the task of detecting and correcting errors in texts as classification or machine translation. Introduced the need to develop a machine-learning algorithm that will take into account the specifics of morphologically complex languages, such as Ukrainian. Demonstrated the work of the modern models and provided screenshots. Revealed the need for further research in the Ukrainian segment of machine learning to solve the problems of correcting errors in texts using various methods and approaches.

THE STATE OF THE ORGANIZATION OF COMMUNICATIVE ACTIVITIES AS A MEANS OF PEDAGOGICAL CORRECTION OF SPEECH ERRORS IN CHILDREN OF THE FIFTH YEAR OF LIFE

The formation of state education and its significant modernization is a consequence of Ukraine’s entry into the European and world educational space. One of the priority tasks of the education system is the upbringing and development of a Ukrainian-speaking personality with a national outlook. Such an individual must possess a single language system of spoken and written Ukrainian texts, must be fluent in various communicative situations, comprehensively contribute to the popularization of the language, ensuring its social prestige. The article is devoted to the study of the state of the organization of communicative activity, which can become an effective means of pedagogical correction of speech errors in children of the fifth year of life both in the conditions of a preschool education institution and in the family, provided that it is properly and managed. The purpose of the research is the analysis of the Basic Component of Preschool Education, current educational programs for preschool institutions for the presence of speech development tasks, as well as a survey of educators and parents of pupils regarding awareness of the concepts of “speech errors”, “speech correction” and ownership of tools for correcting speech mistakes and practicing correct speech.

Determining the ability of artificial intelligence to establish authorship of artistic ukrainian texts using significant fragments

Artificial intelligence is becoming an integral part of everyday life and profes-sional activity of a person. Bing, as an intelligent search system, can serve as a tool for determining the authorship of artistic text in Ukrainian. Bing helps to uncover in-formation about a text fragment and its author, although the search results may be inaccurate or incomplete. This work aims to explore the effectiveness of determining the authorship of ar-tistic texts using modern artificial intelligence tools based on significant fragments of works. Ten Ukrainian authors with a rich body of artistic works, reflecting various as-pects of Ukrainian culture and history, were selected for the experiment. Random fragments up to 500 words in length were selected from various works of these au-thors. An experiment was conducted to determine the authorship of 360 fragments. Using the Python programming language and the skpy package, software was created that sends queries and receives responses from the Bing bot embedded in Microsoft Skype. The presence of the author’s name and the corresponding title of the work were checked in the response texts. This work introduces, for the first time, a method of verifying the authorship of Ukrainian-language text fragments using the Bing bot equipped with artificial intelli-gence. A comparative analysis was conducted and experiments were carried out to identify the authorship of significant long fragments. It was found that long fragments allow the author of the artistic Ukrainian text to be determined with high accuracy. Ivan Franko has the highest percentage of re-sponses where the author’s name and the title of the work were mentioned - 87%. The proposed hypothesis regarding the effectiveness of artificial intelligence in establishing authorship of works has not been confirmed. Artificial intelligence has slightly lower efficiency than expected, which indirectly exposes its means of opera-tion. Namely, when establishing authorship, a sequential research comparison of the proposed fragment with a bank of works that are widespread in the Internet environ-ment is not performed.

LEARNING ACTIVITIES FOR TEACHING PROFESSION SPECIFIC TRANSLATION TO STUDENT TEACHERS OF ENGLISH ON THE TOPIC OF TEACHERS AND LEARNERS: NEW ROLES AND COMPETENCES.

LEARNING ACTIVITIES FOR TEACHING PROFESSION SPECIFIC TRANSLATION TO STUDENT TEACHERS OF ENGLISH ON THE TOPIC OF TEACHERS AND LEARNERS: NEW ROLES AND COMPETENCES.

The Representation of Psychological War-Related Traumas in the Literary Works of Contemporary Burundian and Ukrainian Writers: African and European Perspectives

The article explores the representation of psychological traumas afflicted by war in contemporary literary writing by Burundian (African) and Ukrainian (European) authors who were witnesses of the events described in their works. Based on the existing linguistic and psychological theoretical approaches to the phenomenon of a mental wound, a comparative perspective is provided on the nature, literary, and linguistic manifestations of psychological trauma in Burundian novels by Antoine Kaburahe and Marie-Therese Toyi, presenting the tragic, but stoic experience during the civil war in the East African country, and the shocked, but resilient experience of Ukrainian civilians during the full-scale aggression of the russian federation in the Ukrainian diary (Serhiy Zhadan) and essay writing (Ilya Kaminsky, Ludmila Khersonsky, Zarina Zabrisky, Elena Andreychykova, Andrei Krasniashikh) available in English translation. The implemented analysis allows for a deeper understanding of the effects of wartime psychological trauma on the lives of an individual. Due to a more distant time perspective, the protagonists of Burundian texts reveal both the tragedy of the interethnic civil war conflict and the importance of addressing the causes of the conflict to prevent its replication in the future. In the Ukrainian texts, the initial stage of psychological trauma obtaining can be observed, which accounts for a range of the related emotional states among the characters who do not fully realize yet the traumatization process they have been going through during the first days and weeks of the russian military invasion. The narrative structure of the Burundian and Ukrainian texts was also highlighted, which helped identify traces of oral story-telling tradition (African texts) and broad allusions to the historical and cultural phenomena (Ukrainian texts).

Information System for Ukrainian Text Voiceover Based on Nlp and Machine Learning Methods

During the research, an information system for voicing Ukrainian-language text was developed based on NLP and machine learning methods. The created information system is implemented in the form of a desktop application, which allows the process of voicing the Ukrainian-language text. The created system included all stages of software development: the design process, the implementation process, and the testing process. For the feasibility of creating this system, already existing software solutions on the market were analysed, their advantages and disadvantages were listed, which were subsequently taken into account to create a new system. During the system analysis of the system, a goal tree, a decision tree, and examples of context diagrams with process decomposition are given. One of the stages of the design of the economic part, where the budget that will be spent on the implementation of the system is analysed, all tax and administrative costs are calculated, development strategies are also analysed and the development strategy of the existing product with accompanying solutions and the product development strategy are selected. After that, an assessment was made for the feasibility of creating the designed system, it’s payback and profit. The object of the research is the process of the voiceover system of the Ukrainian-language text based on NLP and machine learning methods. The subject of the research is the methods and means of the Ukrainian-language text voicing system process based on NLP and machine learning methods. The purpose of the research is to create an information system for voicing Ukrainian- language text based on NLP and machine learning methods. The result of the work is a ready-to- implement information system for voicing Ukrainian-language text based on NLP and machine learning methods, an analytical review of literary and online sources related to the topic of voicing Ukrainian- language text based on NLP and machine learning methods, a systematic analysis of the research object, analysis and selection of software tools for system implementation, practical implementation of the system, economic justification of system implementation activities.

SHARED PAIN, THE WAR AND IDENTITY: PECULIARITIES OF UKRAINIAN LITERARY METAMODERNISM

This article examines specific manifestations of the metamodern structure of feeling and features of metamodern poetics represented in contemporary Ukrainian literature, as well as the influence of the state of war, in which Ukraine has been involved since 2014, on the perception of the universal aesthetic characteristics of metamodernism in the national artistic discourse.The global phenomenon of metamodernism is considered in the article in its connections with the previous modernist and postmodern traditions and in the context of the political and cultural processes of the end of the 20th — beginning of the 21th centuries. While scrutinizing Ukrainian fictional works, we referred to the main contemporary research on metamodernism, post-posmodernism, metamodern structure of feeling, and metamodernist aesthetics but the basis of the literary analysis of Ukrainian texts included mainly the studies by Timotheus Vermeulen and Robin van den Akker, Alison Gibbons, Seth Abramson, and Greg Dember. On the basis of their research the specific set of traits of the Ukrainian literary metamodernism was developed, including oscillation, hyper-self-reflexivity, open potentiality as a spatiotemporal characteristic of the artistic worlds, eccentricity of characters («quirky»), ironesty, return of metanarratives (notably, metanarrative of the Ukrainian national identity), attention to influence of media on the identity shaping, imitation of the formal features of postmodernism, the cultivation of immersion in someone else’s felt experience (a «need for a we»), adherence to the ideas of transhumanism and the Anthropocene, cautious optimism and normcore. Despite the unique historical background of the formation of Ukrainian metamodernism (in particular, the persistent attempts of re-colonization of Ukraine by russia during the period of the State Independence, three revolutions and the current war), the key features of this phenomenon in Ukrainian literature are considered to be a «need for a we», hyper-selfreflexivity, and awareness of the importance of a person’s connection with the community.

JENS PETER JAKOBSEN'S NOVELLA “MOGENS” TRANSLATED BY OLHA KOBYLIANSKA: TEXT AND CONTEXTS

The problem of Olha Kobylianska’s interrelationship with European literature has been in the field of researchers’ vision since the Ukrainian author’s appearance in literature. The emergence of new facts related to this problem can accentuate the writer’s conscious focus on mastering the cultural experience of other literatures. O. Kobylianska often emphasized such moments in her own works, naming the authors that influenced her. Among them is the Danish writer Jens Peter Jacobsen. Kobylianska translated Jacobsen’s short story “There Should Have Been Roses” and wrote her original work — a prose poetry “Roses”, containing some allusions and coincidences pointing to the Danish writer’s work. However, this was not the only point connecting the literary worlds of J. P. Yacobsen and O. Kobylianska.
 The other fact of such creative ‘convergence’, unknown until now, is the Ukrainian translation of J. P. Jacobsen’s novella “Mogens” (the unfinished autograph translation is kept in the Manuscript Collections and Textual Studies Department of the Institute of Literature in the fund of Olha Kobylianska under the name “Morene” and with the note “Olha Kobylianska. Unfinished story” (DM ІL, fund 14, folder 1338). The present paper offers attribution of it, including the clarified title and approximate date. The Ukrainian text of the story has been prepared for publication. The inclusion of the incomplete Ukrainian translation of J. P. Jacobsen’s novella into scholarly discourse provides new insights for assessing peculiarities and stylistic parameters of O. Kobylianska’s prose of the late 19th and early 20th centuries. This fact also enhances our understanding of the historical connections between Ukrainian and European literatures, especially Danish literature. The research of O. Kobylianska and J. P. Jacobsen’s works is based on the principles of textual studies, historical-genetic approach, comparative studies, and analytical anthropology.

Development of a web service for creating tests based on text analysis using natural language processing technologies

The purpose of the work is to analyze models, natural language processing methods, and select modern technologies for training these models, as well as to develop a web service for creating tests based on text analysis using natural language processing technologies. The study considers methods and algorithms for intelligent data analysis to generate questions and correct and incorrect answers from the text. The authors justify the choice of a neural network for generating tests based on English and Ukrainian text, and characterize data sources for training. The study also describes the activity of the proposed model, which will serve as a basis for creating a web service. After a detailed review of these datasets, the necessary data for the experiment were extracted and transformed into a convenient format for use. The training algorithm for 6 models was designed and implemented, and valuable metrics were obtained after their training. Additionally, a server-side and web interface were developed to interact with each other.

RUTELA AS A TOOL FOR REVEALING THE POTENTIAL OF UKRAINIAN SCHOOLCHILDREN WHEN STUDYING GERMAN IN AUSTRIA

This article is devoted to the RUTELA project, within the framework of which criteria have been developed that determine the possibilities and potential of a child for the development of German written speech competence. The relevance of this topic is due to the situation, as a result of which more than 10,000 school-age children ended up in Austria and were forced to integrate into the Austrian school system, learn a new foreign language for the majority, and adapt to a new team and teachers. The purpose of this study is to identify the potential of primary schoolchildren with Ukrainian as a native language based on the RUTELA working tool to determine the ability to produce written texts in German. To achieve this goal, a number of tasks were completed: samples of written texts were collected in the classes of an elementary school in the city of Vienna in Ukrainian and German, analysis and interpretation of the data were carried out. The object of the study is the early ability to write in German in elementary school children whose native language is Ukrainian. Identifying the potential of schoolchildren and using it to learn the German language is the subject of the research. Samples of written texts in Ukrainian and German are the material of this study. Elicitation was used as a method, implying actions that encourage the subjects to a productive type of speech activity. The presented study focuses on understanding the development of oral and written literacy in a multilingual environment according to the approach developed by Hans Reich, and also relies on the ELA (Early Literacy Acquisition) working tool, which determines the ability to produce written texts at an early age in Turkish and German. As a result of the analysis of the obtained data, it was possible to establish discrepancies between the realized and actual written competence, as well as to determine the child’s potential for the production of written texts at an early age. The obtained results and their interpretation make it possible to draw up a child’s language profile that describes his abilities, as well as to develop didactic and methodological approaches to support learning both German and his native language.

Data preprocessing and tokenization techniquesfortechnical Ukrainian texts

The field of Natural Language Processing (NLP) has witnessed significant advancements fueled by machine learning, deep learning, and artificial intelligence, expanding its applicability and enhancing human-computer interactions. However, NLP systems grapple with issues related to incomplete and error-laden data, potentially leading to biased model outputs. Specialized technical domains pose additional challenges, demanding domain-specific fine-tuning and custom lexicons. Moreover, many languages lack comprehensive NLP support, hindering accessibility.In this context, we explore novel NLP data preprocessing and tokenization techniques tailored for technical Ukrainian texts. We address a dataset comprising automotive repair labor entity names, known for errors and domain-specific terms, often in a blend of Ukrainian and Russian. Our goal is to classify these entities accurately, requiring comprehensive data cleaning, preprocessing and tokenization.Our approach modifies classical NLP preprocessing, incorporating language detection, specific Cyrillic character recognition, compounded word disassembly, and abbreviation handling. Text line normalization standardizes characters, punctuation, and abbreviations, improving consistency. Stopwords are curatedto enhance classification relevance. Translation of Russian to Ukrainian leverages detailed classifiers, resulting in a correspondence dictionary.Tokenization addresses concatenated tokens, spellingerrors, common prefixes in compound words and abbreviations.Lemmatization, crucial in languages like Ukrainian and Russian, builds dictionaries mapping word forms to lemmas, with a focus on noun cases. The results yield a robust token dictionary suitable for various NLP tasks, enhancing the accuracy and reliability of applications, particularly in technical Ukrainian contexts. This research contributes to the evolving landscape of NLP data preprocessing and tokenization, offering valuable insights for handling domain-specific languages.

Methods of Intellectual Text Analysis

Purpose. Natural language text processing techniques are used to solve a wide range of tasks. One of the most difficult tasks when working with natural language texts for different languages is to find certain indicators for further determining its authorship. The problem is still relevant due to the lack of a unified tool or method for working with texts in different languages. Working with texts in Ukrainian requires taking into account its peculiarities of word and sentence construction to obtain the best result. The main purpose of this article is to analyze the existing methods of text processing, their features and effectiveness in working with texts of different languages. Methodology. Natural language text processing methods are systematized by type and format, according to the tools and approaches used. For each method, its features, effectiveness, scope, and limitations are considered. The means of system analysis were used to form the final characterization of the method, taking into account its purpose and capabilities. Findings. The study of methods has revealed the following ones used for the intellectual analysis of texts in different languages, their scope, effectiveness in working with different languages, strengths and weaknesses. This will make it possible to choose an effective toolkit for working with Ukrainian texts. It has been established that intelligent text processing is a complex task that requires an individual approach to each language to take into account its peculiarities and obtain the best result. Originality. The basis for choosing an effective method for working with Ukrainian-language texts is formed, the existing methods of intellectual text processing, their application features, capabilities and efficiency in working with texts of different languages are analyzed and systematized. Practical value. The work allowed us to identify the most promising, effective and appropriate methods of intellectual analysis of natural language texts in order to use them for processing Ukrainian-language texts in the future.

PECULIARITIES OF TRANSLATING DOUBLETS INTO UKRAINIAN (BASED ON GERMAN AND ENGLISH LEGAL TEXTS)

The article discusses the challenges and strategies of translating doublets into Ukrainian based on German and English legal texts. A corpus-based approach is used to analyze legal texts in two languages to identify the most common types of doublets and determine the most effective ways to translate them into Ukrainian. The study shows that translating doublets in legal texts is a complex process that requires a deep understanding of the source and target languages, as well as the context in which the doublets are used. The results of the study demonstrate that there are several strategies that translators can use to translate doublets effectively. For example, using synonyms, paraphrasing, and omitting one of the components of a doublet pair. These strategies proved to be especially useful when translating doublets from the legal field, as translation in this field requires accuracy and clarity. The practical results of this study are important for translators working with legal texts in German, English and Ukrainian. The study provides valuable insights into the most effective strategies for translating doublets and emphasizes the importance of a thorough understanding of the context in which doublets are used. Moreover, the article has important theoretical importance for researchers in the fields of translation studies, terminology, general and comparative linguistics. The study of doublets on the example of legal texts helps to better understand the mechanisms of translation and the peculiarities of language. The results of the research can be used in further studies of the translation process, including the analysis of other language phenomena and contexts. In particular, it has been found that translating doublets is a complex process that requires a translator to have a deep knowledge of both languages and clear understanding of the context in which doublets are used. In general, the study shows that translation of doublets is an important part of the translation process and requires the translator to be able to follow effective strategies and identify ways to translate doublets.

Stanza-based networks for poetic texts: a pilot study

Abstract We use approaches from the theory of complex networks to analyze the Prologue to Moses, a poem by the Ukrainian writer and scholar Ivan Franko. The Ukrainian text (in the original orthography from 1905 and the modern one) and several translations into Polish, English, French, German, Italian, Portuguese, Slovak, and Spanish are studied. Networks are built in a manner that links are drawn between words (considered network vertices) within a stanza. Seven network parameters are calculated: all-degree centralization, assortativity, average path length, betweenness, clustering coefficient, density, and transitivity. Their dynamics is analyzed as the vertices with the highest numbers of links are removed from the networks one by one. The data obtained for the human-made translations are compared to those based on machine translations generated by the Google Translate service. Peculiarities of certain translations are underlined. Tentative correlation between the values of parameters and levels of language analyticity/syntheticity are established. Prospects toward automatic lemmatization and related problems to be solved are briefly outlined.

Children's book illustrations from China and Ukraine: Comparison of different formats

AbstractThis study was aimed at comparing different formats of illustrations for children's books created by modern Chinese and Ukrainian artists. At the same time, it was not focused just on determining the leading format, but on identifying the attractiveness factors of each format. To this end, the study investigated children's illustration preferences drawing from the following three age groups: 5–6 years old (preschoolers), 7–8 years old (second‐graders), and 9–10 years old (fourth‐graders). According to the survey, children were most concerned with illustration colourfulness (this is true for paper and pop‐up books) and viewing convenience. There were no statistically significant differences found between Chinese and Ukrainian books in terms of these parameters. At the same time, Chinese e‐books appeared to outperform the Ukrainian texts in terms of feature management and illustration colourfulness. Publishers and artists of children's books can use these data for effective creative activity and making constructive decisions. At the same time, these findings may be of interest to parents, informing or guiding book selection for children.