Semantic Word-formation Research Articles

Didactically Relevant Mechanisms of Onym Formation in the Ukrainian Language Today: A Neuropsychological Approach

The article deals with the multifaceted mechanisms of onym formation in the Ukrainian language today and analyzes them in the context of studying linguistic courses and acquiring practical skills in their use. It proves that motivational connections in the language system are found to be typical, regular, regular, which allows us to distinguish several model varieties of lexical and semantic word formation (hereinafter “LSWF”). Only the transfer of the name, in our opinion, should be discussed in the creation of motivated models of onyms. It is simply impossible to talk about any figurative meaning. If we can talk about any transfer, then only about the transfer of a lexical unit from one denotation to another in the presence of speakers permanent (temporary) ideas, ideas about external, functional, spatial or other similarities and proximity of objects - ideas that reflect the real, desired or completely fantasy state of the sphere of the material and spiritual world to which this object belongs. These mechanisms can be analyzed from both linguistic and psycholinguistic (neurolinguistic) points of view. They also objectify universal ways of comprehending and representing a rapidly changing world verbally. Furthemore, the article confirms that the main and most productive models of LSWF at the present stage are derivational metaphor (hereinafter DMF) and derivational metonymy (hereinafter DMT). We consider it possible to use these terms because with the help of DMF and DMT new words are created, not new meanings of words. The use of phrases as a function of proper names (PN) is one of the traditional ways of nomination. Their activation is due to two intralinguistic factors: the tendency to expressiveness and the tendency to maximum motivation of language units.

Naive Bayesian Prediction of Japanese Annotated Corpus for Textual Semantic Word Formation Classification

With the rapid development of Japanese information processing technology, problems such as polysemy and ambiguity at the text and dialogue level, as well as unregistered words, have become increasingly prominent because computers cannot fully “understand” the semantics of words. How to make the computer “understand” the semantics of words accurately requires the computer to “understand” the rules of converting and integrating words into words from the perspective of semantics. Traditional Japanese text classification mostly adopts the text representation method of vector space model, which has the problem of confusing classification effect. Therefore, this paper proposes the topic of constructing a semantic word formation pattern prediction model based on a large-scale annotated corpus. This paper proposes a solution that combines Japanese semantic word formation rules with pattern recognition algorithms. Aiming at this scheme, a variety of pattern recognition algorithms were compared and analyzed, and the naive Bayesian model was decided to predict semantic word formation patterns. This paper further improves the accuracy of computer prediction of Japanese semantic word formation patterns by adding part of speech. Before modeling, the parts of speech of words are automatically tagged and manually checked based on the original annotated corpus. In the research on predicting Japanese semantic word formation patterns, this paper builds a semantic word formation pattern prediction model based on Naive Bayes and conducts simulation experiments. We divide the eight types of semantic word formation patterns in the annotated corpus into two groups, and divide the obtained sample sets into training sets and test sets, so that the Naive Bayes model first learns semantic word formation rules based on the training sets of each group. Semantic word formation patterns are predicted on the test set for each group. The simulation results show that the prediction model of semantic word formation mode has a generally high degree of fit and prediction accuracy. The prediction model of semantic word formation pattern based on this theory can ensure that the computer can judge the semantic word formation pattern more accurately.

Prediction of Chinese Semantic Word-Building Patterns Based on Complex Network Features

The research on prediction of Chinese semantic word-formation patterns based on complex network features has certain practical and theoretical significance in the field of natural language understanding. In this paper, complex networks are introduced into the prediction of Chinese semantic word-formation patterns, and a new prediction method of Chinese semantic word-formation patterns based on complex networks is proposed. And a solution that combines the semantic word-building rules of Chinese language with pattern recognition algorithm is put forward. Aiming at this scheme, a variety of pattern recognition algorithms are compared and analyzed, and the most suitable binary logistic regression model and naive Bayes model are found to predict Chinese semantic word-building patterns. The semantic loss is reduced, and the text classification model and corresponding classification algorithm are constructed, by introducing the maximum common subgraph theory to calculate text similarity under the complex network representation. The results of the experiments show that using complex networks to predict Chinese semantic word-formation patterns is both effective and feasible. The computer can judge the semantic word-formation pattern more accurately using the semantic word-formation pattern prediction model based on this theory.

PANDEMIC LEXIS IN THE MODERN ENGLISH MEDIA LANDSCAPE

The outburst of the COVID-19 pandemic has brought forth replenishment of the Mass Media lexis. The paper aims at studying new word formation trends in the semantic field of COVID-19 in the English Media Landscape. The study of coinages connected with the coronavirus disease has the following goals: to determine ways of their word formation, word-building models and to single out their productive types. Analysis of neologisms related to the coronavirus disease has shown that current limitations in people’s social lives have a strong impact on their communication and on their choice of language means and tools in particular. New elements of on-line communication: innovations in paralinguistic means and stylistic neologization of the Internet discourse suggest the appearance of a new communicative genre. New coinages associated with COVID-19 are divided into the three thematic groups. The first class includes medical terms that replenished common lexis and nominations, belonging to the regulations of people’s lives; the second group is represented by lexical innovations of mundane character, which sometimes have their colloquial equivalents; the third category covers jocular words related to the topic of the coronavirus disease. The findings of the investigation allow us to make a conclusion that the potential of telescopy, affixation, clipping and abbreviation as of major word-forming ways is retained, and that the role of compounding and composition in coining of split nominations (word combinations) is increasing. New mixed abbreviation types have been described, the emergence of their new derivatives has been registered. The data also show that English has become a donor for other languages providing terms-internationalisms (e.g. lockdown, sanitizer). Semantic word formation on the material of coinages from the English Internet discourse is attested by metaphorisation of common lexis. Determinization of medical lexemes and processes of lexical units’ migration between the different linguistic styles of English can be retraced.

СЛОВОТВІРНІ ОСОБЛИВОСТІ ПРАСЛОВ’ЯНСЬКИХ СОМАТИЗМІВ

The naming of body parts, acting as one of the most noticeable layers of vocabulary, which reflects the knowledge of native speakers about the world around them, and their idea of both their own body and the body of animals, is the subject of constant attention of linguists. In modern linguistics, as in the humanities in general, the anthropocentric approach to the separation of somatic vocabulary prevails, when only parts of the human body are included in body parts. However, such a view of the realm of the corporeal and, moreover, the understanding of the pair “somatic – mental” only as one that applies to a man, denies the corporeality (however, as well as the realm of the psyche) of other living organisms ‒ animals. Therefore, we consider it appropriate to include the names of body parts of animals as somatic names. The article found that the Proto-Slavic language had a fairly extensive system of names of body parts. Many somatisms called parts of the body of both humans and animals. The somatic lexical subsystem includes such large groups of nouns to denote parts of the human and animal body, as: sonymic, osteonymic, splanchnonymic, angionimic, myonymic, sensonymic, neoplasmonimic. The object of study is the vocabulary to denote parts of the human and animal body, including the name of the head and its parts, neck and torso, skeleton and bones, cardiovascular and circulatory system, internal organs, muscles, human and animal senses, and also the names of neoplasms recorded in monuments of different styles and genres and historical dictionaries that reflect the vocabulary of the Proto-Slavic period. The purpose of the article is to carry out word-formation analysis of somatic names in the history of the Ukrainian language of the Proto-Slavic era. The main research methods are descriptive, comparative-historical, structural (component) analysis. The description of somatic names is carried out according to a complex method that combines semantic-word-forming and etymological aspects of the study. The authors found that the derivation of somatic names in the Proto-Slavic language occurred in two ways: by morphological and semantic word formation. The most productive, among morphological, way of word formation of somatic names of the pre-written period was suffixation, much less active in derivation of new words was confixation, prefix and composite word formation was represented by single formations. The peculiarity of the derivational semantics of somatisms on the territory of ancient Slavia is that some formants already lost their diminutive meaning in pre-written times. Non-morphological methods were represented by semantic derivation, when somatisms were created by transferring meaning on the basis of similarity, which later laid the foundations for the formation of a significant layer of somatic vocabulary. Prospects for the study are a more detailed analysis of the development and formation of somatic names in the dialects of the Ukrainian language, as well as the creation of principles for concluding a terminological basis of natural, including medical, sphere based on specific Ukrainian lexical material.

Semantico-Functional Features of Expressive Derivatives in the Artistic Discourse of V. Makanin

The paper is devoted to the study of semantic and functional features of expressive derivatives, both usual and occasional, in the artistic gist of the novel “Asan” by V. Makanin, as well as their role in structuring the individual-author’s linguistic picture of the world. It has been proven that the derivation of expressive lexemes is the result of improvisation according to established patterns, and that the formation of occasional substantives, adjectives and verbs involved the main methods of the Russian word derivation. It is noted that in the artistic discourse of V. Makanin, in the substantive word-formation, suffixation plays a leading role, which takes place in the sphere of abstractness and includes such lexical-semantic groups as expressive substantives with the meaning of a person, expressive substantives with the meaning of abstracted action or an abstract feature with connotation, as a rule, negative and/or reduced colloquial connotation. While in the sphere of adjectival and verbal word formation, confixation and prefixation, as the formation of expressiveness, is most productive. The paper considers the phenomenon of semantic word formation, describes the formation of semantic derivatives, including in the field of occasional vocabulary. Expressive derivatives in the artistic discourse of V. Makanin are a bright sign of his individual style, an important means of expressing the world view and outlook of the writer.

Grammatical and Semantic Word-Formation of Toponymic Derivatives (on the Material of the Toponym “CИБИPЬ”)

The paper presents morphemic-derivational structure of toponymic derivatives (toponymy-derived formations) of proper name “Cибирь”. In revealed derived words authors identify morphemes, specify the methods of their production, provide statistics on word-formation activity of morphemes in the process of secondary nomination of toponymy-derived appellatives. Based on regional material of dialectal dictionaries they define the peculiarities of toponym’s word-formation family of words, as well as its paradigmatic relations with derived categories. Horonym “Cибирь” is considered in the context of perception by regional linguistic persona in the national toponymic space. Examples of semantic toponymy-derived word-formation are given. Thereby, in Russian language world picture it is possible to identify a set of regionally marked background knowledge, perceptions of values as well as historical and cultural characteristics of the analyzed toponym.

Prediction of Chinese word-formation patterns using the layer-weighted semantic graph-based KFP-MCO classifier

Nowadays natural language processing plays an important and critical role in the domain of intelligent computing, pattern recognition, semantic analysis and machine intelligence. For Chinese information processing, to construct the predictive models of different semantic word-formation patterns with a large-scale corpus can significantly improve the efficiency and accuracy of the paraphrase of the unregistered or new word, ambiguities elimination, automatic lexicography, machine translation and other applications. Therefore it is required to find the relationship between word-formation patterns and different influential factors, which can be denoted as a classification problem. However, due to noise, anomalies, imprecision, polysemy, ambiguity, nonlinear structure, and class-imbalance in semantic word-formation data, multi-criteria optimization classifier (MCOC), support vector machines (SVM) and other traditional classification approaches will give the poor predictive performance. In this paper, according to the characteristic analysis of Chinese word-formations, we firstly proposed a novel layered semantic graph of each disyllabic word, the layer-weighted graph edit distance (GED) and its similarity kernel embedded into a new vector space, then on the normalized data MCOC with kernel, fuzzification and penalty factors (KFP-MCOC) and SVM are employed to predict Chinese semantic word-formation patterns. Our experimental results and comparison with SVM show that KFP-MCOC based on the layer-weighted semantic graphs can increase the separation of different patterns, the predictive accuracy of target patterns and the generalization of semantic pattern classification on new compound words.

Author’s Interpretation of Toponyms of the Historical Sources and the Hagiographic Literary Works

Geographical names give us lots of noteworthy information about the historical, geographical, political, economic, religious, cultural, etc. picture of a denotation. Due to this the onomastic data are the valuable sources to study the history, language, dialectology, geography, geology, archeology and ethnography of a country. In Georgia one hardly find a small place without a name. Towns, hamlets, villages, groves, gardens, vineyards, arable fields, hills, mountains, water, grassland, former settlements and sometimes trees, rocks and large rocks are given names. Researchers interested in geographical names accept two basic ways of origin of toponyms: 1. either via the toponimization of appellatives without derivation (which is called semantic word-formation: changing of a lexeme’s status, while the form remains unchangeable) or derivation: 2.transonimization of proper names: transition from one onymic class to another as well as transtoponimization, transhydronimization, and a transoikonymization, etc. The toponyms originated via the first (toponimization) method is called the primary toponyms, and the ones originated via the second (transonimization) method - secondary toponyms. The research goal is to study an author’s interpretation and semantic properties of the geographic names of hagiographic works and historical sources of the 5-10th cc. In the sources under research the authors give us not only the information on the location of any geographic object, but they offer a noteworthy explanation of some toponyms and microtoponyms as well. An author’s etymology has extra linguistic and linguistic character and therefore it is of scientific importance, the motivation - persuasive. Existing standpoints on location and explanation of some geographical names (Darialani, Tsertaisni, Satakhve, Zarzma, Garedja, Divri, Tskhenistsqali) are represented in comment form. On the basis of analyzed material the paper demonstrates that the ancient Georgian artistic and historical written sources show the ways and means of origin of toponyms. The cited episodes highlight the basic principle of toponymic word-derivation - the contents of a name is relevant to an object’s name. This is achieved via the following the grammatical means: 1. elision (either determinatum or determinandum component is elided: tsertaisni ! adgilni tsertaisni; bakta ! adgili bakta). 2. derivation (Sataxve – structurally it is a derived form); 3. word-amalgamation (Sheshistavi, Zarzma, Gareja… are structurally compound two-component entries).

On the Basic Problems of the Category of Aktionsart in the Russian Language

The article summarizes the basic questions of aktionsart (the status, content, and borders of the category) in the Russian language and describes the most relevant views on the problem. In the author’s opinion, the category of aktionsart is a semantic-word formation category, one that includes motivated verbs with formal markers of semantic change of the base verb, except for verbs of motion. Taking into consideration that word formation models are polysemic, the verb classes of aktionsart can be specified not by formal factors but by semantic ones. Consequently, the content of the category of aktionsart is determined by word formation and semantics together. Another key problem is the connection between the category of aktionsart and category of grammatical aspect and the sphere of word formation. The author joins the opinion of those linguists who consider aktionsart to be the lexical level of the macrocategory of aspect. The category of aktionsart is separated from the sphere of word formation by the regularity of verb formation. Regarding this criteria, as the author suggests, some verb formation models of low regularity should not be acknowledged as verb classes of aktionsart.

Chinese Semantic Word-Formation Analysis Using FKP-MCO Classifier Based on Layered and Weighted GED

For Chinese information processing, automatic classification based on a large-scale database for different patterns of semantic word-formation can remarkably improve the identification for the unregistered word, automatic lexicography, semantic analysis, and other applications. However, owing to noise, anomalies, nonlinear characteristics, class-imbalance, and other uncertainties in word-formation data, the predictive performance of multi-criteria optimization classifier (MCOC) and other traditional data mining approaches will rapidly degenerate. In this paper we put forward an novel MCOC with fuzzification, kernel, and penalty factors (FKP-MCOC) based on layered and weighted graph edit distance (GED): firstly the layered and weighted GEDs between each semantic word-formation graph and prototype graphs are calculated and used for the dissimilarity measure, then the normalized GEDs are embedded into a new feature vector space, and FKP-MCO classifier based on the feature vector space is built for predicting the patterns of semantic word-formation. Our experimental results of Chinese word-formation analysis and comparison with support vector machine (SVM) show that our proposed approach can increase the separation of different patterns, the predictive performance of semantic pattern of a new compound word.