Semantic Structure
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Morphology ◽  
2021 ◽  
Fritz Günther ◽  
Marco Marelli

AbstractMany theories on the role of semantics in morphological representation and processing focus on the interplay between the lexicalized meaning of the complex word on the one hand, and the individual constituent meanings on the other hand. However, the constituent meaning representations at play do not necessarily correspond to the free-word meanings of the constituents: Role-dependent constituent meanings can be subject to sometimes substantial semantic shift from their corresponding free-word meanings (such as -bill in hornbill and razorbill, or step- in stepmother and stepson). While this phenomenon is extremely difficult to operationalize using the standard psycholinguistic toolkit, we demonstrate how these as-constituent meanings can be represented in a quantitative manner using a data-driven computational model. After a qualitative exploration, we validate the model against a large database of human ratings of the meaning retention of constituents in compounds. With this model at hand, we then proceed to investigate the internal semantic structure of compounds, focussing on differences in semantic shift and semantic transparency between the two constituents.

Marina Sukhomlinova ◽  

The academic lecture is considered to be one of the basic genres of modern English-language academic discourse. The study of the compositional structure of the lecture text is extremely important, since a correctly arranged composition contributes to a better presentation of the topic by the lecturer and systemic learning of the material by the students. The purpose of this research was to identify the compositional features of the text of the English-language academic lecture. To achieve this goal, eight English-language lectures on the humanities were selected and carefully analysed. In the course of the analysis, phases of the lecture were singled out, the hierarchy of its elements was revealed, and the composition matrix of the lecture text was built. The main compositional elements of the lecture are as follows: the pre-text part (title complex), the text part (introduction, body, and conclusion) and the aftertext part (references and expression of gratitude for attention). As a result, the author proved that the lecture text has a matrix structure, whose elements are nonuniform, each being designed to perform its own specific function. The compositional-semantic structure of the lecture captures the movement from the “old” knowledge to the “new”. Further, English-language lectures demonstrate both strong and weak positions. This means that some elements in the text are more important than others. At the same time, the strong position does not have to be rigidly connected with the structure of the text. The following are regarded as strong positions: title of the lecture, names of its subsections, beginning and end of subsections, introductory and closing parts of the lecture, conclusions, semantic repetitions of key information, questions-and-answers part, and in-text references.

2021 ◽  
Vol 11 (9) ◽  
pp. 1025-1033
Jinan Al-Tamimi

The acquisition of the ability of perceiving and naming colors through language is an important topic in which languages vary and differ. The construction of color concepts and naming them are directly influenced by the culture and environment of each society. This can be noted by observing two aspects: Cognitive Semantics and its effect on the collective mind. This study focuses on the cognitive foundations of color terms in Arabic, and the semantic relation between the color concepts and terms in selected examples from both old and new usage of these color terms in Arabic. The study aims to cover the most dominant semantic components for color terms in the Arabic language, using the cognitive linguistic approach and the descriptive analytics method to determine the structure of cognitive perception of color terms in a language. Furthermore, the study stands on two pillars; the first reveals the way the conceptualization pattern of color terms occurs in Arab mindset displayed through selected examples of theoretical data on cognitive semantics, whereas the second addresses the semantic principle of color classification in Arabic. Finally, the conclusion, confirming the results about the notion that color naming in Arabic is based on the visual images associated with the colors in Arab environment, related to night and day. Hence, the color term becomes connected in the Arab mindset with the visual image, and under each color are colors similar to it in hue.

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2123
Raúl Tárraga-Mínguez ◽  
Julio Tarín-Ibáñez ◽  
Irene Lacruz-Pérez

A textbook constitutes the hegemonic material of the educational institution. It acts as a mediator between the official curriculum and the educational practice. Given its potential influence in the classroom, this study analyzes the treatment of word problems included in the mathematics textbooks published by the publishing houses with the greatest diffusion in Spain at every primary education grade. Three variables were analyzed: their semantic structure, their degree of challenge, and their situational context. The results indicate that most of the problems included in textbooks are characterized by low complexity and variability regarding their semantic structure. They are also characterized by a limited degree of challenge and by being presented in highly standardized situational contexts. Likewise, it is found that there is no evolution in the treatment of these problems with respect to previous studies carried out in the Spanish context. Therefore, it is concluded that the mathematics textbooks currently used in schools are not effective tools to address the process of teaching-learning problem solving.

Q. Wang ◽  
M. Hou ◽  
S. Lyu

Abstract. Mural painting is one of the important cultural heritage reflecting the historical migration of the nation. In order to inherit these precious historical and cultural heritage, how to non - destructively and digitally protect and restore the existing murals has become an urgent task. The use of computer - assisted restoration of murals can not only save manpower and material resources, but also avoid secondary damage to the murals.However, most of the existing computer-assisted mural restoration algorithms use similar blocks with priority calculations and matching blocks in adjacent areas to guide mural restoration. There are some problems such as incoherent overall semantic structure, unnatural detail texture and inability to effectively repair large area missing remain to be solved. Aiming at the problems existing in the restoration of large area diseases such as paint loss and color fading in murals, we constructed a fine image restoration network model which based on generative adversarial network. A multi-scale dense matching repair network based on a generative adversarial network is constructed. First, the dense combination of dilated convolutions is used to improve the repair effect of detailed textures, Then, mean absolute Error, (Visual Geometry Group, VGG) feature matching, auto-guided regression, and geometric alignment are used as the loss function to guide the training of the generative network. Second, the discriminator with local and global branches is used to train the discriminant network, so that the repaired image is in the local and global content. Experiments were performed on the three mural data sets one by one. The results show that the network model can effectively restore the lines and faces in the murals. The images restored are not only coherent in semantic details, but also natural in color, which is conducive to the appreciation and display of murals. Thus, as one of the important directions of cultural heritage digital protection,the use of generative adversarial network in the digital restoration of ancient murals have been proved to be effective. It not only provides a reference for the true restoration of the murals but also means a lot to the preservation of murals.

A. De Masi

Abstract. The study illustrates a university research project of “Digital Documentation’s Ontology”, to be activated with other universities, of an Platform (P) – Building Information Modeling (BIM) articulated on a Contaminated Hybrid Representation (diversification of graphic models); the latter, able to foresee categories of Multi-Representations that interact with each other for to favour several representations, adapted to a different information density in the digital multi-scale production, is intended as platform (grid of data and information at different scales, semantic structure from web content, data and information storage database, archive, model and form of knowledge and ontological representation shared) of: inclusive digital ecosystem development; digital regenerative synergies of representation with adaptable and resilient content in hybrid or semi-hybrid Cloud environments; phenomenological reading of the changing complexity of environmental reality; hub solution of knowledge and simulcast description of information of Cultural Heritage (CH); multimedia itineraries to enhance participatory and attractive processes for the community; factor of cohesion and sociality, an engine of local development. The methodology of P-BIM/CHR is articulated on the following ontologies: Interpretative and Codification, Morphology, Lexicon, Syntax, Metamorphosis, Metadata in the participatory system, Regeneration, Interaction and Sharing. From the point of view the results and conclusion the study allowed to highlight: a) Digital Regenerative synergies of representation; b) Smart CH Model for an interconnection of systems and services within a complex set of relationships.

2021 ◽  
Vol 11 (17) ◽  
pp. 7782
Itziar Urbieta ◽  
Marcos Nieto ◽  
Mikel García ◽  
Oihana Otaegui

Modern Artificial Intelligence (AI) methods can produce a large quantity of accurate and richly described data, in domains such as surveillance or automation. As a result, the need to organize data at a large scale in a semantic structure has arisen for long-term data maintenance and consumption. Ontologies and graph databases have gained popularity as mechanisms to satisfy this need. Ontologies provide the means to formally structure descriptive and semantic relations of a domain. Graph databases allow efficient and well-adapted storage, manipulation, and consumption of these linked data resources. However, at present, there is no a universally defined strategy for building AI-oriented ontologies for the automotive sector. One of the key challenges is the lack of a global standardized vocabulary. Most private initiatives and large open datasets for Advanced Driver Assistance Systems (ADASs) and Autonomous Driving (AD) development include their own definitions of terms, with incompatible taxonomies and structures, thus resulting in a well-known lack of interoperability. This paper presents the Automotive Global Ontology (AGO) as a Knowledge Organization System (KOS) using a graph database (Neo4j). Two different use cases for the AGO domain ontology are presented to showcase its capabilities in terms of semantic labeling and scenario-based testing. The ontology and related material have been made public for their subsequent use by the industry and academic communities.

Kashif Munir ◽  
Hai Zhao ◽  
Zuchao Li

The task of semantic role labeling ( SRL ) is dedicated to finding the predicate-argument structure. Previous works on SRL are mostly supervised and do not consider the difficulty in labeling each example which can be very expensive and time-consuming. In this article, we present the first neural unsupervised model for SRL. To decompose the task as two argument related subtasks, identification and clustering, we propose a pipeline that correspondingly consists of two neural modules. First, we train a neural model on two syntax-aware statistically developed rules. The neural model gets the relevance signal for each token in a sentence, to feed into a BiLSTM, and then an adversarial layer for noise-adding and classifying simultaneously, thus enabling the model to learn the semantic structure of a sentence. Then we propose another neural model for argument role clustering, which is done through clustering the learned argument embeddings biased toward their dependency relations. Experiments on the CoNLL-2009 English dataset demonstrate that our model outperforms the previous state-of-the-art baseline in terms of non-neural models for argument identification and classification.

2021 ◽  
Vol 20 (6) ◽  
pp. 247-262
E. N. Ermolaeva ◽  
N. V. Potapova

Nowadays the study of media text pragmatics is one of the research priorities in media linguistics. The pragmatic potential of a media text is actualized through the symbiosis of its verbal, nonverbal, and multimedia components, which are equally capable of having a powerful impact on mass consciousness. The article focuses on the linguovisual pragmatics of the so-called “pulled-out” elements in English-language Internet media texts, which have not been studied so far. A pulled-out element is a graphically emphasized construction within a media text, containing a very short summary of the topic covered in the article, or quotations with different references describing the position of the journalist, participants of the event or experts towards the topic, or containing additional information. Following their functional orientation and type of graphical display, the pulled-out elements are divided into three main types: callouts, pull quotes, block quotes. At the graphic level, all three types are represented by a font and font size different from the article itself; they are often located to the left or in the center of the article and can be highlighted with a colored background. The linguistic representation of the pulled-out elements is determined by their functional nature: a simple but pragmatically effective syntactic and semantic structure of the included sentences is used, in most cases implementing the “clickbait” principle. The type, content, and quantity of the pulled-out elements used depend on the genre specifics and linguistic properties of the media text. The pulled-out elements of the media text perform a number of functions, the main of which are informative, attractive, affective, integrative, and ideological. It is stated that the pulled-out elements, being an integral attribute of the modern media text and one of the ways of its creolization, effectively incorporate verbal and nonverbal (graphic) components to have a multi-layered pragmatic impact on the recipient. A comprehensive study of the nature of this phenomenon, regarding its actualization at the structural and semantic levels, is necessary and relevant for media linguistics at the present stage of its development. 

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