Language Sentences Research Articles

Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 5. Introduction to Logic

Introduction. The article continues the series of publications on the linguistics of relations (hereinafter R–linguistics) and is devoted to an introduction to the logic of natural language in relation to the approach considered in the series. The problem of natural language logic still remains relevant, since this logic differs significantly from traditional mathematical logic. Moreover, with the appearance of artificial intelligence systems, the importance of this problem only increases. The article analyzes logical problems that prevent the application of classical logic methods to natural languages. This is possible because R-linguistics forms the semantics of a language in the form of world model structures in which language sentences are interpreted.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations in the field of logic and semantics, the formulated concept of the interpretation operator is used.Results and discussion. The problems that arise when studying the logic of natural language in the framework of R–linguistics are analyzed. These issues are discussed in three aspects: the logical aspect itself; the linguistic aspect; the aspect of correlation with reality. A very General approach to language semantics is considered and semantic axioms of the language are formulated. The problems of the language and its logic related to the most General view of semantics are shown.Conclusion. It is shown that the application of mathematical logic, regardless of its type, to the study of natural language logic faces significant problems. This is a consequence of the inconsistency of existing approaches with the world model. But it is the coherence with the world model that allows us to build a new logical approach. Matching with the model means a semantic approach to logic. Even the most General view of semantics allows to formulate important results about the properties of languages that lack meaning. The simplest examples of semantic interpretation of traditional logic demonstrate its semantic problems (primarily related to negation).

A Sanskrit-to-English machine translation using hybridization of direct and rule-based approach

The work in this paper presents a MTS from Sanskrit to English language using a hybridized form of direct and rule-based machine translation technique. This paper also discusses the language divergence among Sanskrit and English languages with a recommended solution to handle the divergence. The proposed system has used two bilingual dictionaries (Sanskrit–English, Sanskrit–UNL), a tagged Sanskrit corpus, a Sanskrit analysis rule base and an ELGR base. Elasticsearch technique has enhanced the translation speed of the proposed system for accessing the data from different data dictionaries and rule bases used for the system development. The system uses CFG in CNF for Sanskrit language processing and CYK parsing technique for processing the input Sanskrit sentence. This work also presents a novel algorithm which creates a parse tree from the parsing table. ELGR base and bilingual dictionaries generate the target language sentence. The proposed system is evaluated using natural language toolkit API in python and achieved a BLEU score of 0.7606, fluency score of 3.63 and adequacy score of 3.72. A comparison of the proposed system with state-of-the-art systems shows that the proposed system outperforms existing systems.

Modeling the Relationships between Language Skills and Sentence Comprehension among Chinese Junior Elementary Graders

The present study examined the contributions of vocabulary knowledge, syntactic skills, and oral narrative skills to sentence reading comprehension among Chinese junior elementary school children. Various language and reading measures were administered to 85 Chinese normally-achieving children at Grades 2 and 3 in Hong Kong. Results showed that vocabulary knowledge and oral narrative skills contributed significantly to word order skills, an important syntactic skill in Chinese. Vocabulary knowledge contributed to word recognition directly and contributed to sentence comprehension indirectly through word recognition and syntactic skills; and syntactic skills contributed to sentence comprehension directly. These findings suggest that while vocabulary knowledge is important for Chinese word reading, syntactic word order plays a central role in Chinese sentence comprehension. The implications of these findings for our theoretical understanding of the Simple View of Reading, as well as reading instruction, will be discussed.

Theorizing about the Syntax of Human Language

Linguists standardly assume that a grammar is a formal system that ‘generates’ a set of derivations. But this is not the only way to formalize grammars. I sketch a different basis for syntactic theory: model-theoretic syntax (MTS). It defines grammars as finite sets of statements that are true (or false) in certain kinds of structure (finite labeled graphs such as trees). Such statements provide a direct description of syntactic structure. Generative grammars do not do this; they are strikingly ill-suited to accounting for certain familiar properties of human languages, like the fact that ungrammaticality is a matter of degree. Many aspects of linguistic phenomena look radically different when viewed in MTS terms. I pay special attention to the fact that sentences containing invented nonsense words (items not in the lexicon) are nonetheless perceived as sentences. I also argue that the MTS view dissolves the overblown controversy about whether the set of sentences in a human language is always infinite: many languages (both Brazilian indigenous languages and others) appear not to employ arbitrarily iterative devices for embedding or coordination, but under an MTS description this does not define them as radically distinct in typological terms.

Using deep neural networks and biological subwords to detect protein S-sulfenylation sites.

Protein S-sulfenylation is one kind of crucial post-translational modifications (PTMs) in which the hydroxyl group covalently binds to the thiol of cysteine. Some recent studies have shown that this modification plays an important role in signaling transduction, transcriptional regulation and apoptosis. To date, the dynamic of sulfenic acids in proteins remains unclear because of its fleeting nature. Identifying S-sulfenylation sites, therefore, could be the key to decipher its mysterious structures and functions, which are important in cell biology and diseases. However, due to the lack of effective methods, scientists in this field tend to be limited in merely a handful of some wet lab techniques that are time-consuming and not cost-effective. Thus, this motivated us to develop an in silico model for detecting S-sulfenylation sites only from protein sequence information. In this study, protein sequences served as natural language sentences comprising biological subwords. The deep neural network was consequentially employed to perform classification. The performance statistics within the independent dataset including sensitivity, specificity, accuracy, Matthews correlation coefficient and area under the curve rates achieved 85.71%, 69.47%, 77.09%, 0.5554 and 0.833, respectively. Our results suggested that the proposed method (fastSulf-DNN) achieved excellent performance in predicting S-sulfenylation sites compared to other well-known tools on a benchmark dataset.

Changing Internet Language Features Among the Korean Scholarly Group

This study aims at identifying how the Korean scholarly group's internet language features changed during the last 10 years. For this study, 2,450 written texts on the same web-site in which a previous study collected data were analyzed. This comparison study showed the following results: 1)First of all, the scholarly group's internet texts still involved standard language, high-quality vocabulary and long sentences; 2)However, it was very difficult to find Chinese characters and the percentage of the usage of English increased significantly; 3)Presenting objective data and numbering were still frequently seen; 4)Furthermore, typical internet languages such as slang, argot and abbreviations began to appear; 5)Texts showing self-reflection and teaching tone have been decreased. Instead, texts implying psychological pressure and worries about their jobs have increased; 6)The biggest change was that most of communicator's names were written in English (or unidentified words) or commonly used internet names. This study concludes that comparing to the previous study, the scholarly group's internet language features have changed (although some based on occupational variables remained the same), and that these changes might be affected by social changes taking place in the scholarly group.

The Use of Japanese Adjectives Ureshii and Tanoshii

This study is a semantic study that explores the genre of meaning in general. It focuses on the synonyms of adjectives ureshii and tanoshii in the construction of sentences in the Japanese language. The objective of this study is to discuss similarities and differences of the usage of synonyms ureshii and tanoshii and also to analyse the implementation from the perspective of adjectives in the Malay language. The data selected for this study are sentences that contained ureshii and tanoshii lexicons based on Shinmeikai Japanese Language Dictionary (2012). This study utilizes qualitative research methodology in which the data are analysed descriptively. Besides that, the data are also analysed using textual analysis based on the conceptual framework by Ibrahim Ahmad (2005). The findings of this study elucidate the technical differences in the usage of Japanese adjectives ureshii and tanoshii as compared to Malay adjectives gembira [happy] and seronok [excited]. It shows that the two adjectives have similar meaning and nuance but cannot be used interchangeably. The outcomes of this study can be used as reference material for teachers and students to master the usage of adjectives in Japanese language. Lastly, further studies on Japanese lexicon keiyoushi should be carried out entirely.

KONTRASTIVITAS DIATESIS PASIF BAHASA INDONESIA DAN BAHASA JEPANG DALAM DONGENG JEPANG MOMOTARŌ

This study aims at (1) describing the rules of the passive voice in Indonesian and Japanese languages, (2) finding the markers of passive sentences in Indonesian and Japanese languages, (3) describing the similarities and differences of passive sentences in Indonesian and Japanese. The data is collected by the descriptive method. The method of data analysis is a contrastive analysis. The result of data analysis is presented by method Indonesian passivization explained by the change of morphology on the verb, for example, Indonesian language passive using markers di-, ter- and ke-an. Meanwhile, Japanese language passivization is described by verbs and nouns functioning as objects in passive sentences. Japanese verbs consist of consonant verbs, vowel verbs, and irregular verbs. Passive sentences in the Japanese language are marked by marker ni + V-areru for consonant verbs, markers ni + V-areru for vocal verbs, ni + V-areru for irregular verbs, and ni + yotte V-areru/V-rareru for verbs that are followed as object inanimate nouns. Similarly, there are two passivizations in Japanese: passivization using the direct object and the indirect object. However, the indirect passivization of the Japanese can use transitive verbs or intransitive verbs. Japanese passive sentences express the completion of an action and an unpleasant meaning. In comparison, the Japanese passive sentence is not used as regularly as Indonesian passive because Japanese passive tends to express a point of view first person. In addition, another difference between passive sentences in Indonesian and Japanese is that in Japanese it is important to know the subject.

Yakup Kadri Karaosmanoğlu’nun “Hep O Şarkı” Adlı Romanında Soru Cümleleri

الغرض من البحث:
 الجمل الاستفهامية هي من الجمل
 في بحثنا هذا تناولنا الجمل الاستفهامية في رواية الاغنية للكاتب يعقوب قدري قارا عثمان ولا أهمية هذه الرواية بين الروايات التركية ولغناها بالجمل الاستفهامية وقع اختيارنا عليها.

A Survey of the Model Transfer Approaches to Cross-Lingual Dependency Parsing

Cross-lingual dependency parsing approaches have been employed to develop dependency parsers for the languages for which little or no treebanks are available using the treebanks of other languages. A language for which the cross-lingual parser is developed is usually referred to as the target language and the language whose treebank is used to train the cross-lingual parser model is referred to as the source language. The cross-lingual parsing approaches for dependency parsing may be broadly classified into three categories: model transfer, annotation projection, and treebank translation. This survey provides an overview of the various aspects of the model transfer approach of cross-lingual dependency parsing. In this survey, we present a classification of the model transfer approaches based on the different aspects of the method. We discuss some of the challenges associated with cross-lingual parsing and the techniques used to address these challenges. In order to address the difference in vocabulary between two languages, some approaches use only non-lexical features of the words to train the models while others use shared representations of the words. Some approaches address the morphological differences by chunk-level transfer rather than word-level transfer. The syntactic differences between the source and target languages are sometimes addressed by transforming the source language treebanks or by combining the resources of multiple source languages. Besides cross-lingual transfer parser models may be developed for a specific target language or it may be trained to parse sentences of multiple languages. With respect to the above-mentioned aspects, we look at the different ways in which the methods can be classified. We further classify and discuss the different approaches from the perspective of the corresponding aspects. We also demonstrate the performance of the transferred models under different settings corresponding to the classification aspects on a common dataset.

Effects of age on American Sign Language sentence repetition.

The study of deaf users of signed languages, who often experience delays in primary language (L1) acquisition, permits a unique opportunity to examine the effects of aging on the processing of an L1 acquired under delayed or protracted development. A cohort of 107 congenitally deaf adult signers ages 45-85 years who were exposed to American Sign Language (ASL) either in infancy, early childhood, or late childhood were tested using an ASL sentence repetition test. Participants repeated 20 sentences that gradually increased in length and complexity. Logistic mixed-effects regression with the variables of chronological age (CA) and age of acquisition (AoA) was used to assess sentence repetition accuracy. Results showed that CA was a significant predictor, with increased age being associated with decreased likelihood to reproduce a sentence correctly (odds ratio [OR] = 0.56, p = .010). In addition, effects of AoA were observed. Relative to native deaf signers, those who acquired ASL in early childhood were less likely to successfully reproduce a sentence (OR = 0.42, p = .003), as were subjects who learned ASL in late childhood (OR = 0.27, p < .001). These data show that aging affects verbatim recall in deaf users of ASL and that the age of sign language acquisition has a significant and lasting effect on repetition ability, even after decades of sign language use. These data show evidence for life-span continuity of early life effects. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The Function of Nominalizing Particle NO as Modifier and Nominalizer in Japanese Language Sentence

Particle no in Japanese language sentence has some functions as modifier, nominalizer, and feminine marker. In this research, the researcher investigated the function of particle no as modifier and nominalizer in Japanese language sentence. Referring to term used by Shibatani et al. (2017), particle no with such function is called juntai joushi no or nominalizing particle no. This research aims to grammatically elaborate the nominalization process in Japanese language sentence with marker of nominalizing particle no. Research methodology used was qualitative descriptive using data source in form of news published in NHK (2020). Data analysis was conducted using theory as stated by Morita (2013), Shibatani et al. (2017) and Shibatani &amp; Chung (2018). Research shows the result that the nominalizing particle no serves as modifier when attached to noun or noun phrase and nominalizer when attached to verbal clause. Function of the nominalizing particle no as modifier provides additional meaning to main noun with structure which consists of additional noun, nominalizing particle no, and main noun. Additional noun is more than one. Meanwhile, the nominalizing particle no as nominalizer changes the form of verbal clause into noun phrase, so it can be topic, subject, and object in Japanese language sentence with structure of verbal clause, nominalizing particle no, and particles which mark topic, subject, or object.

Different kinds of embodied language: A comparison between Italian and Persian languages

It is debated whether only concrete but also abstract, figurative sentences, e.g.: “She grasps the cup” vs. “She grasps the concept”, are grounded in the sensorimotor system. Importantly, studies on sentences with action verbs and motor system activation have been conducted so far only with WEIRD samples (Western cultures, in North American and European countries). The aim of our work is to investigate the relationship between language and motor responses using both concrete and abstract sentences in Italian and Persian languages. In the present study, Italian and Persian participants were asked to read the sentences on the screen. The sentences referred either literally or metaphorically to motor actions. They were accompanied by a video displaying a movement that could be congruent or incongruent with the one described in the sentence. Participants were asked to re-execute the movement observed and subsequently they had to perform the task evaluating whether the sentence made sense or not. In the Italian sample a strong effect of concreteness was present, especially in the congruent but also in the incongruent condition. In the Persian sample, instead, there was an inhibition effect of congruent trials, particularly with concrete sentences, and in the incongruent trials no difference in RTs between abstract and concrete sentences was present. Results indicate that cross-cultural differences have to be taken into account when investigating the relationship between language and action.

Development of the Hong Kong Sign Language Sentence Repetition Test.

This paper presents the design and development of the Hong Kong Sign Language-Sentence Repetition Test (HKSL-SRT). It will be argued that the test offers evidence of discriminability, reliability, as well as practicality and can serve as an effective global measurement of individuals' proficiency in HKSL. The full version of the test consists of 40 signed sentences of increasing length and complexity. Specifically, we will evaluate the manual and non-manual components of these sentences to find out whether and to what extent they can differentiate three groups of deaf signers, namely, native signers, early learners and late learners. Statistical analyses show that the test scores based on a correct repetition of the manual signs of each sentence bear a significant negative correlation with signers' age of acquisition. Including the correct repetition of non-manuals in the scoring scheme can result in higher reliability and separation index of the test in the Rasch model. This paper will also discuss how psychometric measures of Rasch analysis, including the concept of fit and the rankings of items/persons in the Wright map, have been applied to the original list of the 40 sentence items for the development of a shortened test.

STUDI GEOGRAFI IMAGINATIF DALAM PROSES PEMBELAJARAN BIPA

Abstrak&#x0D; Hubungan ideologis pada proses pembelajaran bahasa Indonesia untuk penutur asing (BIPA) tidak dapat dielakkan, karena program BIPA adalah sebuah program yang berelasi dengan banyak pembauran budaya di dalamnya. Bentuk bahasa (kata, kalimat, dan variasi bahasa) adalah bagian dari faktor keberhasilan pengetahuan bagi pembelajarnya sebagai penerima konvensi. Bahasa tanpa karakteristik budaya sama artinya dengan mempelajari bentuk gramatikal semata tanpa memperhatikan makna. Sementara, inti dari berbahasa ialah apabila komunikasi yang terjalin dipahami karena adanya makna dari bahasa itu sendiri. Artikel ini menjelaskan kemungkinan pola belajar dari titik geografi imajinatif untuk menyoroti dan membangun identitas bahasa Indonesia yang dipelajari melalui pendekatan Orientalisme Edward Said. Persepsi persoalan bahasa yang dipelajari dan konstuksi identitas penutur yang mempelajarinya menjadi sebuah fenomena, hingga peran geografi imajinatif menjadi penting. Ide dasar dalam artikel ini adalah mendesposisikan pengalaman belajar dan mengajar menjadi strategi yang terpolakan sebagai langkah awal dalam memahami karakteristik pembelajaran BIPA melalui dasar-dasar pengenalan dan pengetahuan geografi imajinatif dalam prosesnya. Dalam hal ini, ide belajar bahasa biasanya mempertimbangkan kekuatan kelas serta tingkat kebutuhan terhadap bahasa yang dipelajari. Studi tentang otoritas kelinguistikan dibahas dengan menggunakan metode referensial, di dalamnya pembelajar bahasa asing menghadapi genre teks budaya secara umum. Dua instrumen metodologis digunakan untuk menelaah lebih jauh, yaitu memperhatikan karakateristik pembelajar BIPA dengan menggunakan perangkat formasi strategis dan posisi strategis.&#x0D; &#x0D; Kata Kunci: Geografi imajinatif, Pembelajaran BIPA, Metode Formasi Strategis, Metode Posisi Strategis&#x0D; &#x0D; Abstract&#x0D; The ideological relationship in the Indonesian language learning process for foreign learning (BIPA) is inevitable, because the BIPA program is a program related to much cultural assimilation there. The form of language (sentences, sentences, and variations of language) is part of the success factors of knowledge for students as convention recipients. Language without cultural characteristics is synonymous with grammatical form features only without regard to meaning. Meanwhile, the core of the conversation about communication is intertwined because of the meaning of the language itself. This article explains about learning patterns from the point of imaginative geography to discuss and build Indonesian language identity which is learned through the discussion of Edward Said's Orientalism. The perspective of the language learned and the construction of the identity of the speakers who study it become a phenomenon, so the role of imaginative geography becomes important. The basic idea in this article exposes the experience of learning and teaching into a strategy that is thought of as a first step in understanding the characteristics of BIPA through the basics of knowledge and knowledge imaginative geography in the process. In this case, the idea of ​​learning a language usually considers class and the level of need for the language being studied. The study of linguistics authority is discussed using referential methods, in which language expenditures translate cultural texts in general. Two methodological instruments are used to explore further, namely paying attention to the characteristics of BIPA spending using strategic formation and strategic positions tools.&#x0D; Keywords: Imaginative Geography, BIPA Learning, Strategic Formation Methods, Strategic Position Methods

Measuring text similarity based on structure and word embedding

The problem of finding the similarity between natural language sentences is crucial for many applications in Natural Language Processing (NLP). An accurate calculation of similarity between sentences is highly needed. Many approaches depend on word-to-word similarity to measure sentence similarity. This paper proposes a new approach to improve the accuracy of the sentence similarity calculation. The proposed approach combines different similarity measures in the calculation of sentence similarity. In addition to traditional word-to-word similarity measure, the proposed approach exploits sentence semantic structure. Discourse representation structure (DRS) which is a semantic representation for natural sentences is generated and used to calculated structure similarity. Furthermore, word order similarity is measured to consider the order of words in sentences. Experiments show that exploiting structural information achieves good results. Moreover, the proposed method outperforms the current approaches on a standard benchmark dataset achieving 0.8813 Pearson correlation with human similarity.

Visualization Classification and Prediction Based on Data Mining

The paper aims to solve huge amounts and noise of current internet information. In order to better excavate the user’s interests and provide accurate recommendations, improve the Internet environment and services and accurately analyze and evaluate the behavior of large-scale user groups. This article compares web pages with sentences in natural language, and uses the natural language processing algorithm Word2vec to extract the feature vectors of massive web pages browsed by users. PCA has been reduced to two dimensions, and webpage visualization and logistic regression have been implemented to classify webpages. A series of user clicks on webpages can be viewed as a walk in n-dimensional space. Probabilistic language models and Monte Carlo simulations are used as the next step for users. Click behavior to make predictions. Experiments show that the machine learning processing natural language algorithm used in this paper has a good performance in classification and prediction accuracy.

Morphosyntactic adaptation in adult L2 processing: Exposure and the processing of case and tense violations

AbstractThis paper investigates morphosyntactic adaptation in second language (L2) sentence processing. In a pre-/posttest control group design, two experiments with intermediate to advanced German–English learners examine whether massed exposure to informative input leads to adaptation in L2 processing in that L2 readers come to integrate inflection in real-time comprehension. Experiment 1 on case marking shows that input causing prediction error and flagging the target parse leads to nativelike integration of case in the reanalysis of garden-path sentences. Experiment 2 shows partially nativelike processing of adverbial–verb tense mismatches after exposure to target input. Adaptation was selective to the experimental versus the control group in processing, yet it did not generalize to offline, explicit performance. We conclude that morphosyntactic adaptation constitutes an implicit learning mechanism in L2 processing, and we discuss its implications for models of L2 processing and acquisition.

Índices entonativos de modalidad entre enunciados declarativos e interrogativos con final descendente: variedades geoprosódicas de Asturias

This paper shows the relevance of the tonal range and the duration as complementary intonation indices of the pitch accents and boundary edges in the discrimination of declarative and interrogative sentences in languages with falling boundary tones in both modalities. It is based on regularities observed in the prosodic descriptions, verified in perceptual experiments and assessed by dialectometric analysis in the geoprosodic varieties of Asturias. The different models and, especially, the one of Asturian centromeridional are shown in which the concatenation of pitch accents and boundary edges is identical in the assertive and interrogative utterances. The samples from the Asturian corpus of the Atlas Multimedia Prosodico del Espacio Romanico (AMPER-Astur) are taken as a reference.

DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model

Strong passwords are fundamental to the security of password-based user authentication systems. In recent years, much effort has been made to evaluate password strength or to generate strong passwords. Unfortunately, the usability or memorability of the strong passwords has been largely neglected. In this paper, we aim to bridge the gap between strong password generation and the usability of strong passwords. We propose to automatically generate textual password mnemonics, i.e., natural language sentences, which are intended to help users better memorize passwords. We introduce \textit{DeepMnemonic}, a deep attentive encoder-decoder framework which takes a password as input and then automatically generates a mnemonic sentence for the password. We conduct extensive experiments to evaluate DeepMnemonic on the real-world data sets. The experimental results demonstrate that DeepMnemonic outperforms a well-known baseline for generating semantically meaningful mnemonic sentences. Moreover, the user study further validates that the generated mnemonic sentences by DeepMnemonic are useful in helping users memorize strong passwords.