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The article is devoted to the issue of word-formation motivation, which does not lose its relevance and plays a role not only in disclosing formal-semantic relations between words of one language and has not only theoretical, but also applied significance. The authors consider word-formation motivation consistently in its varieties in a comparative way on the materials of so different languages as Russian and Arabic and approach the mechanism of achieving semantic equivalence of translation. To the greatest extent, word-formation activity today, due to objective reasons, affects some special branch (technical, medical, etc.) vocabulary, which is increasing from year to year in national dictionaries. This extensive material, selected by the authors, not only illustrates the current trends in word formation in modern languages, but also provides an answer to the question about the degree of equivalence of this subgroup of words in Russian and Arabic. The goal to compare word-formation motivation according to a number of criteria in different-structured languages made possible not only to obtain theoretical information about what features each of the languages has in word formation and what derivational potential it has, but also to reveal an algorithm for translating derived words from one language to another. For this, the authors complete a number of such particular tasks as highlighting significant elements in the neologisms of the Russian and Arabic languages, establishing standards for the formation of scientific and terminological vocabulary in Arabic, searching for tools (transformation operations, specific word-formation formants) that will contribute to the achievement of translation equivalence from Russian to Arabic, etc. Also the analysis of differences in the mechanisms of the formation of new vocabulary in the Russian and Arabic languages provided an opportunity to supplement the relatively young and rapidly developing private methodology of Russian-Arabic translation.

This study reports on recent changes in the use of the hedges kind of and sort of in spoken British English over the past twenty years. A quantitative analysis of these features within subsets of the original BNC 1994 (BNC Consortium 2007) and BNC 2014 (Love et al. 2017) suggests a systematic encroaching of kind of into contexts that are traditionally occupied by sort of. This is highlighted in apparent-time patterns in which younger speakers are leading in use as well as real-time patterns that show a significant increase in use between 1994 and 2014.The hedges sort of and kind of are often treated as semantically equivalent, yet show distributional differences across different varieties of English. This article reports on an ongoing shift in the use of kind of as well as a relatively stable use of sort of. Its main focus is a detailed sociolinguistic analysis of both variants, which, in addition to social factors involved, teases apart some of the linguistic aspects of this shift.In line with the theme of this special issue, the article draws attention to the usefulness of comparable, or comparably made, corpora that allow for focused studies of linguistic change across speakers, generations, registers and communities.

Web API/service technology has been attracting considerable attention and the REST (REpresentational State Transfer) architecture is now widely accepted as mainstream technology. Nonetheless, developing the means by which to discover RESTful Web APIs/services is crucial to the further development of this technology. Unfortunately, existing search engines for RESTful Web APIs/services provide only keyword-based or tag-based search functions. A failure to take into account the semantics and/or characteristics (e.g., their interface compatibility) greatly hampers the ability to find suitable APIs/services. In this study, we propose a novel approach to the discovery of RESTful Web API/services, referred to as Test-Oriented API Search with Semantic Interface Compatibility (TASSIC). This scheme involves expanding the terms of Web API/service documents based on DBpedia and WordNet. Unsuitable APIs/services are then filtered out using a systematic process, as follows: 1) calculation of semantic similarity between a set of candidate APIs/services and a user query, 2) analysis of interface compatibility between candidate APIs/services using the Hungarian Algorithm, 3) invocation of candidate APIs/services to verify functionality and availability, and 4) analysis of similarity between the actual response of the candidate services and the expected response specified in the user query. The proposed TASSIC increases the likelihood of matching APIs/services that are semantically equivalent or similar to user queries. Unit test and acceptance test are used to verify that a set of candidate APIs/services are actually available and that they actually meets user requirements. Experiment results demonstrate the efficacy of TASSIC, the accuracy of which is superior to that of existing methods.

Determining the extent to which two text snippets are semantically equivalent is a well-researched topic in the areas of natural language processing, information retrieval and text summarization. The sentence-to-sentence similarity scoring is extensively used in both generic and query-based summarization of documents as a significance or a similarity indicator. Nevertheless, most of these applications utilize the concept of semantic similarity measure only as a tool, without paying importance to the inherent properties of such tools that ultimately restrict the scope and technical soundness of the underlined applications. This paper aims to contribute to fill in this gap. It investigates three popular WordNet hierarchical semantic similarity measures, namely path-length, Wu and Palmer and Leacock and Chodorow, from both algebraical and intuitive properties, highlighting their inherent limitations and theoretical constraints. We have especially examined properties related to range and scope of the semantic similarity score, incremental monotonicity evolution, monotonicity with respect to hyponymy/hypernymy relationship as well as a set of interactive properties. Extension from word semantic similarity to sentence similarity has also been investigated using a pairwise canonical extension. Properties of the underlined sentence-to-sentence similarity are examined and scrutinized. Next, to overcome inherent limitations of WordNet semantic similarity in terms of accounting for various Part-of-Speech word categories, a WordNet “All word-To-Noun conversion” that makes use of Categorial Variation Database (CatVar) is put forward and evaluated using a publicly available dataset with a comparison with some state-of-the-art methods. The finding demonstrates the feasibility of the proposal and opens up new opportunities in information retrieval and natural language processing tasks.

Objective: To translate and back-translate the Consumer Financial Protection Bureau (CFPB) Financial Well-Being Scale into Brazilian Portuguese, to assess its cross-cultural semantic equivalence, and to verify the psychometric properties of the final version. Methods: Adaptation of the original scale applied a three-step methodology: translation and back-translation, appreciation of semantic equivalence, and administration to a convenience sample of 834 subjects. The analysis of psychometric properties comprised evaluation of evidence of the instrument’s validity by factor analysis, validity by contrasting groups, and internal consistency with Cronbach’s alpha coefficient. The CFPB granted authorization to conduct cross-cultural adaptation into Brazilian Portuguese. Results: Results indicated adequate cultural adaptation between scales, with good equivalence between the original English version and the final Brazilian version. The Cronbach’s alpha coefficient for the instrument’s internal consistency in this sample was 0.89. Exploratory and confirmatory factor analyses demonstrated high levels of item reliability and goodness of fit, with all 10 items loading onto a single factor, financial well-being. The measure has shown structural stability in two different cultural contexts (Brazil and the USA). Conclusion: The Brazilian version demonstrated acceptable psychometric properties and adequate structural and cross-cultural validity and the participants found it easy to understand.

In many languages a string comparison is a pitfall for beginners. With any Unicode string as input, a comparison often causes problems even for advanced users. The semantic equivalence of different characters in Unicode requires a normalization of the strings before comparing them. This article shows how to handle Unicode sequences correctly. The comparison of two strings for equality often raises questions concerning the difference between comparison by value, comparison of object references, strict equality, and loose equality. The most important aspect is semantic equivalence.

The proposed work is focused on establishing an interpretable Semantic Textual Similarity (iSTS) method for a pair of sentences, which can clarify why two sentences are completely or partially similar or have some variations. This proposed interpretable approach is a pipeline of five modules that begins with the pre-processing and chunking of text. Further chunks of two sentences are aligned using a one–to–multi (1:M) chunk aligner. Thereafter, support vector, Gaussian Naive Bayes and k–Nearest Neighbours classifiers are then used to create a multiclass classification algorithm, and different class labels are used to define an alignment type. At last, a multivariate regression algorithm is developed to find the semantic equivalence of an alignment with a score (that ranges from 0 to 5). The efficiency of the proposed method is verified on three different datasets and also compared to other state–of–the–art interpretable STS (iSTS) methods. The evaluated results show that the proposed method performs better than other iSTS methods. Most importantly, the modules of the proposed iSTS method are used to develop a Textual Entailment (TE) method. It is found that, when we combined chunk level, alignment, and sentence level features the entailment results significantly improves.

Objective: The Back Pain Functional Scale (BPFS) was designed to evaluate the functional state of individuals with low back pain. The scale consists of twelve items, covering functional aspects of the daily life activities of these individuals. The final score is calculated by summing the responses to each item, the values of which range from 0 to 5, obtaining a total result of 0 to 60 points. Methods: The validation process was developed in accordance with the World Health Organization (WHO) protocol, covering translation, back translation, semantic equivalence, evaluation by specialists from previous stages, pre-test of the tool, and final version. Subsequently, the final version was applied in a sample of 90 individuals and the data obtained were subjected to descriptive statistical analysis, factorial analysis, evaluation of internal consistency, and correlation with other validated tools. Results: The tool was adapted to Brazilian Portuguese, making use of terms to approximate the language of everyday expressions. The final version presented results similar to those from the original version, as demonstrated by the factorial analysis, the internal consistency (Cronbach's alpha: 0.990), and the strong correlation with tools validated for the Portuguese language. Conclusion: The Brazilian version of BPFS proved to be easy to apply and understand, and presented high internal consistency and construct validity similar to that of the original instrument. Level of evidence 1B; Study of adaptation of a valid score.

The present descriptive study aimed at investigating the human and machine Persian translations of The Kite Runner by Khalid Hosseini, and comparing the applied translation strategies in the translated texts for culture-specific items (CSI). To this end, based on Newmark’s (1988) category, the applied strategies were identified in the two translations and compared. The obtained results showed that Naturalization and Transposition strategies were the most frequently-used strategies by both human translators and machine translation. The results also showed that machine translation could not present a comprehensible translation due to overuse of these strategies (75%). It was further revealed that the spirit of the original text was not lost in the translated versions due to the closeness of Iranian and Afghan cultures. In fact, the translated versions kept the real beauty and creativity of the original work. However, the remorseful theme of the source text was kept intact to a great extent in the human translation of the novel, while machine translation lost it. Thus, the general impression is that culture-specific terms make it difficult for the machine translation to achieve complete word-for-word and semantic equivalence, and that the human translator must have a broad knowledge of the literature and traditions of both the source and target languages.

Recently, there exist growing concerns about the interpretability of deep learning models. While few of these models have been applied to a duplicate question detection task, which aims at finding semantically equivalent question pairs of question answering forum. In this paper, based on an attention mechanism, we propose two modularized interpretable deep neural network models for such tasks. During the word precessing procedure, a filter operation is employed to enhance the relevant information contained in the pre-trained word embeddings. Regarding the word matching and sentence representation process, vanilla attention and structured attention mechanisms are utilized, respectively. Benefiting from the interpretability of attention techniques, our models can illustrate how the words match between sentence pairs and what aspects of the sentences are extracted to have an effect on the final decision. The attention visualization furnishes us with detailed representation at word and sentence level. And experimental results show that our models are comparable with other reported models.

Most high performance general purpose processors leverage register renaming to implement optimizations such as move elimination or zero-idiom elimination. Those optimizations can be seen as forms of strength reduction whereby a faster but semantically equivalent operation is substituted to a slower operation. In this letter, we argue that other reductions can be performed dynamically if input values of instructions are known in time, i.e., prior to renaming. We study the potential for leveraging Value Prediction to achieve that goal and show that in SPEC2k17, an average of 3.3 percent (up to 6.8 percent) of the dynamic instructions could dynamically be strength reduced. Our experiments suggest that a state-of-the-art value predictor allows to capture 59.7 percent of that potential on average (up to 99.6 percent).

Human languages contain a variety of tools for referencing agents, locations, arguments of predicates, and other entities that are introduced, described, and attributed actions within sentences. While there are similarities across modalities, there also exist notable differences. For example, signed languages are articulated with two hands, and sometimes one of them serves referencing functions while the other produces complementary signs. Additionally, signers use role shift and constructed action extensively, whereas there is comparatively less use of reported speech and co-speech enactment in spoken language discourse. Differences across modalities such as these provide areas of focus for studies of interpretation, since a common theoretical premise is that interpreters should disengage from the form of a source-language message in order to provide the meaning in the target language (with its own form). It is open to debate whether an interpretation can achieve complete semantic equivalence, given differences in the grammars, lexical items, and discourse features of the source- and target-languages. We use Libras texts interpreted into Brazilian Portuguese to examine various types of referencing in language and how it occurs in such texts. Our analysis is intended to raise questions about referencing and interpretation that merit in-depth study.-----------------------------------------------------------------------------ALTERNÂNCIA DE REFERÊNCIA NAS LÍNGUAS DE SINAIS E LÍNGUAS FALADAS: CARACTERÍSTICAS GRAMATICAIS E DISCURSIVAS ENTRE MODALIDADES EM INTERPRETAÇÕES DE LIBRAS PARA LÍNGUA PORTUGUESAAs línguas humanas contêm uma variedade de ferramentas para referenciar agentes, locais, argumentos de predicados e outras entidades que são introduzidas, descritas e atribuídas com ações nas sentenças. Embora existam semelhanças entre as modalidades, também existem diferenças notáveis. Por exemplo, as línguas de sinais são articuladas com duas mãos, e às vezes uma delas tem funções de referência enquanto a outra produz sinais complementares. Além disso, o sinalizador usa a alternância de referência e a ação construída extensivamente, enquanto há comparativamente menos uso de cotação e ação construída que co-ocorre com discurso da língua falada. Diferenças entre modalidades como essas fornecem áreas de foco para estudos da interpretação, uma vez que uma premissa teórica comum é que os intérpretes devem se desvincular da forma de uma mensagem na língua de origem a fim de fornecer o significado na língua de destino (com sua própria forma). É possível debater se uma interpretação pode alcançar equivalência semântica completal, dadas as diferenças nas gramáticas, itens lexicais e características do discurso das línguas-fonte e as línguas-alvo. Usamos textos de Libras interpretados para o português brasileiro para examinar vários tipos de referência nessas línguas e como ela ocorre nesses textos. Nossa análise pretende levantar questões sobre referenciação e interpretação que merecem um estudo aprofundado.---Origina em inglês.

Several formalisms for language syntax specification exist in literature. In this paper, we prove that longstanding syntactical transformations between context-free grammars and algebraic signatures are adjoint functors and/or adjoint equivalences that preserve the abstract syntax of the generated terms. The main result is a categorical equivalence between the categories of algebras (i.e., all the possible semantics) over the objects in these formalisms up to the provided syntactical transformations, namely that all these language specification frameworks are essentially the same from a semantic perspective.

This paper suggests that xiē ‘some’ in Mandarin Chinese originated as a quantifier but became a classifier in the yi ‘one’ construction via realignment, or change in inheritance in diachronic construction grammar. This change has created yi xiē, semantically equivalent to xiē, therefore it is also a case of reinforcement in the sense of Jespersen’s Cycle. However, this study argues that yi xiē has not necessarily undergone grammaticalisation. Generalising the analysis, two types of reinforcement are proposed: reinforcement by innovation and by realignment. The former involves grammaticalisation, but the latter may not. The study highlights the importance of higher-level generalisations in language change.

Sob a ótica da Gramática Cognitiva (LANGACKER, 1987; 1991), este trabalho investiga o polo semântico de duas construções nominais de referência genérica do português brasileiro: [Artigo + Nome Singular] (“O gato é voluntarioso”) e [Ø + Nome Singular] (“Gato é voluntarioso”). Propõe-se que, apesar da identidade extensional, as duas construções não são semanticamente equivalentes. Especificamente, sustenta-se que o padrão com artigo, mas não o padrão sem artigo, facultaria a conceptualização de um conjunto de tipos não perfilados no interior de um Espaço de Tipo. Para verificar essa hipótese, desenvolveu-se um experimento de julgamento de aceitabilidade no qual os participantes avaliaram a naturalidade de sentenças contendo SNs singulares genéricos em contextos contrastivos nas condições com e sem artigo definido. Os resultados mostraram diferença significativa de aceitabilidade entre as duas condições (p = 0,0014), o que fornece evidências em favor da hipótese de que os padrões construcionais investigados, de fato, evocam representações mentais distintas.

Dans cet article, nous discutons de certains problèmes liés à la modélisation de la variation et du changement linguistique dans le cadre théorique de la Grammaire Cognitive des Constructions. Nous remettons notamment en cause le principe de non synonymie tel que proposé par Goldberg (1995, 2006), principalement en ce qui concerne l’indistinction entre les composantes sémantique et pragmatique dans la définition de construction. Pour cela, nous analysons les constructions causales por causa de et por conta de afin de montrer que dans certains contextes elles peuvent alterner. Bien que les deux constructions jouent des rôles argumentatifs différents, elles partagent un ensemble de propriétés formelles et sémantiques qui engendrent un espace de variation, surtout si on restreint l’ équivalence sémantique au niveau référentiel. Les résultats de l’analyse permettent d’apporter des arguments favorables à une définition plus stricte du principe de non synonymie.------------------------------------------------------------------------------------------HA LUGAR PARA VARIAÇÃO NA GRAMATICA DE CONSTRUÇÕES COGNITIVA? O CASO DA CONSTRUÇÃO [por SN de X]Neste artigo, discutimos alguns problemas relativos à modelização da variação e da mudança linguística no quadro teórico da Gramática de Construções Cognitiva. Colocamos em causa, em especial, o princípio da não sinonímia tal como formulado por Goldberg (1995, 2006), principalmente no que se refere à indistinção entre os componentes semântico e pragmático na definição de construção. Para tanto, analisamos as construções causais intraoracionais por causa de e por conta de, com o objetivo de mostrar que elas podem alternar em alguns dos seus contextos. Embora as duas construções desempenhem funções argumentativas distintas, elas partilham um conjunto de propriedades formais e semânticas que criam um espaço de variação, principalmente se restringimos equivalência semântica ao nível referencial. Os resultados obtidos na análise fornecem evidências para argumentar a favor de uma delimitação mais estrita do princípio de não sinonímia.---Original em francês.

Answer Set Programming (ASP) is a declarative logic formalism that allows to encode computational problems via logic programs. Despite the declarative nature of the formalism, some advanced expertise is required, in general, for designing an ASP encoding that can be efficiently evaluated by an actual ASP system. A common way for trying to reduce the burden of manually tweaking an ASP program consists in automatically rewriting the input encoding according to suitable techniques, for producing alternative, yet semantically equivalent, ASP programs. However, rewriting does not always grant benefits in terms of performance; hence, proper means are needed for predicting their effects with this respect. In this paper we describe an approach based on Machine Learning (ML) to automatically decide whether to rewrite. In particular, given an ASP program and a set of input facts, our approach chooses whether and how to rewrite input rules based on a set of features measuring their structural properties and domain information. To this end, a Multilayer Perceptrons model has then been trained to guide the ASP grounder I-DLV on rewriting input rules. We report and discuss the results of an experimental evaluation over a prototypical implementation., Comment: In Proceedings ICLP 2020, arXiv:2009.09158

Modern cyber attacks are often conducted by distributing digital documents that contain malware. The approach detailed herein, which consists of a classifier that uses features derived from dynamic analysis of a document viewer as it renders the document in question, is capable of classifying the disposition of digital documents with greater than 98% accuracy even when its model is trained on just small amounts of data. To keep the classification model itself small and thereby to provide scalability, we employ an entity resolution strategy that merges syntactically disparate features that are thought to be semantically equivalent but vary due to programmatic randomness. Entity resolution enables construction of a comprehensive model of benign functionality using relatively few training documents, and the model does not improve significantly with additional training data. In particular, we describe and quantitatively evaluate a fully automated, document format--agnostic approach for learning a classification model that provides efficacious malicious document detection.

Recently, many Resource Description Framework (RDF) data generation tools have been developed to convert geospatial and non-geospatial data into RDF data. Furthermore, there are several interlinking frameworks that find semantically equivalent geospatial resources in related RDF data sources. However, many existing Linked Open Data sources are currently sparsely interlinked. Also, many RDF generation and interlinking frameworks require a solid knowledge of Semantic Web and Geospatial Semantic Web concepts to successfully deploy them. This article comparatively evaluates features and functionality of the current state-of-the-art geospatial RDF generation tools and interlinking frameworks. This evaluation is specifically performed for cultural heritage researchers and professionals who have limited expertise in computer programming. Hence, a set of criteria has been defined to facilitate the selection of tools and frameworks. In addition, the article provides a methodology to generate geospatial cultural heritage RDF data and to interlink it with the related RDF data. This methodology uses a CIDOC Conceptual Reference Model (CRM) ontology and interlinks the RDF data with DBpedia. Although this methodology has been developed for cultural heritage researchers and professionals, it may also be used by other domain professionals.

Formally identical terminological units belonging to related languages can demonstrate both coincidence and divergence in semantics and stylistic correlation - due to linguistic reasons, as well as extralinguistic factors generated by the legal processes of a particular state. All this complicates the legal translation procedure, which means that it requires a detailed legal and linguistic analysis of such units. The article provides rationale for the systematization and comprehensive description of formally matching interlanguage correspondences of Slavic and non-Slavic origin, in which at least one lexical unit belongs to the legal terminology of the Russian or Bulgarian language. The terminological pairs with the same plan of expression identified and equally expressed in the modern Russian and Bulgarian legislation are placed on a scale of semantic correspondences as follows: zero (false) semantic equivalence - partial semantic similarity - full semantic equivalence. It is noted that particular difficulties can be correlated with the translation of formally identical terms-derived words that arose from the same elements based on the same word-formation model, as this makes their semantic mismatch not so obvious. The analysis of specific examples demonstrates that in closely related languages different units of parallel intralinguistic synonymic series can be codified, and therefore ignoring aspects of the word's functioning in the language leads to lexical and semantic interference in translation. The author concludes that a comparative study of interlanguage parallels in Russian and Bulgarian legal terminology is important for solving problems of lexicography and legal translation., Формально тождественные терминологические единицы, принадлежащие родственным языкам, могут демонстрировать как совпадение, так и расхождение в семантике и стилистической соотнесенности – в силу собственно лингвистических причин, а также под влиянием экстралингвистических факторов, порождаемых правовыми процессами конкретного государства. Все это осложняет процедуру юридического перевода, а значит, требует детального юридико-лингвистического анализа подобных единиц. В статье обосновывается необходимость систематизации и комплексного описания формально совпадающих межъязыковых соответствий славянского и неславянского происхождения, в которых хотя бы одна лексическая единица принадлежит юридической терминологии русского либо болгарского языка. Выявленные в современном российском и болгарском законодательстве терминологические пары с одинаковым планом выражения распределяются по шкале семантических соответствий, включающей следующие уровни отношений: нулевая (ложная) семантическая эквивалентность – частичное семантическое сходство – полная семантическая эквивалентность. Отмечается, что особые трудности могут быть связаны с переводом формально тождественных терминов-девербативов, возникших из одних и тех же элементов на основе одной и той же словообразовательной модели, так как это делает их семантическое несовпадение не столь очевидным. Анализ конкретных примеров демонстрирует, что в близкородственных языках кодификации могут быть подвергнуты разные единицы паралельных внутриязыковых синонимических рядов, в связи с чем игнорирование аспектов функционирования слова в языке приводит к лексико-семантической интерференции. Автор приходит к выводу, что сопоставительное исследование межъязыковых параллелей в русской и болгарской юридической терминологии имеет важное значение для решения актуальных задач лексикографии и юридического перевода.