Linguistic Rules Research Articles

Employing a Multilingual Transformer Model for Segmenting Unpunctuated Arabic Text

Long unpunctuated texts containing complex linguistic sentences are a stumbling block to processing any low-resource languages. Thus, approaches that attempt to segment lengthy texts with no proper punctuation into simple candidate sentences are a vitally important preprocessing task in many hard-to-solve NLP applications. To this end, we propose a preprocessing solution for segmenting unpunctuated Arabic texts into potentially independent clauses. This solution consists of: (1) a punctuation detection model built on top of a multilingual BERT-based model, and (2) some generic linguistic rules for validating the resulting segmentation. Furthermore, we optimize the strategy of applying these linguistic rules using our suggested greedy-like algorithm. We call the proposed solution PDTS (standing for Punctuation Detector for Text Segmentation). Concerning the evaluation, we showcase how PDTS can be effectively employed as a text tokenizer for unpunctuated documents (i.e., mimicking the transcribed audio-to-text documents). Experimental findings across two evaluation protocols (involving an ablation study and a human-based judgment) demonstrate that PDTS is practically effective in both performance quality and computational cost. In particular, PDTS can reach an average F-Measure score of approximately 75%, indicating a minimum improvement of roughly 13% (i.e., compared to the performance of the state-of-the-art competitor models).

Peningkatan Hasil Belajar Siswa pada Materi Teks Berita Melalui Model Pembelajaran Silent Game

The completeness of students' cognitive learning outcomes on news text material, especially in linguistic sub-rules, is very low because the learning model is not yet precise. This article aims to improve students' cognitive learning outcomes on news text material in the linguistic rules sub-material with the silent game learning model. The method used is Classroom Action Research with two cycles. Each cycle is carried out in one meeting. The results showed a significant increase in cognitive learning outcomes. Furthermore, there was an increase in the absorption of students from cycle I to cycle II of 18.66. Meanwhile, learning completeness increased by 75% and completeness of objectives and material subjects by 100%. It concludes that the silent game learning model can improve the students' cognitive learning outcomes.

Automatic Classification of Eyewitness Messages for Disaster Events Using Linguistic Rules and ML/AI Approaches

Emergency response systems require precise and accurate information about an incident to respond accordingly. An eyewitness report is one of the sources of such information. The research community has proposed diverse techniques to identify eyewitness messages from social media platforms. In our previous work, we created grammar rules by exploiting the language structure, linguistics, and word relations to automatically extract feature words to classify eyewitness messages for different disaster types. Our previous work adopted a manual classification technique and secured the maximum F-Score of 0.81, far less than the static dictionary-based approach with an F-Score of 0.92. In this work, we enhanced our work by adding more features and fine-tuning the Linguistic Rules to identify feature words related to Twitter Eyewitness messages for Disaster events, named as LR-TED approach. We used linguistic characteristics and labeled datasets to train several machine learning and deep learning classifiers for classifying eyewitness messages and secured a maximum F-score of 0.93. The proposed LR-TED can process millions of tweets in real-time and is scalable to diverse events and unseen content. In contrast, the static dictionary-based approaches require domain experts to create dictionaries of related words for all the identified features and disaster types. Additionally, LR-TED can be evaluated on different social media platforms to identify eyewitness reports for various disaster types in the future.

ANALYSIS OF THE WEBTOON DIGITAL COMMIC LANGUAGE RULES ”FUNNY LIFE IS” AND ITS IMPLICATIONS AS A MEDIA FOR Anecdotal TEXT LEARNING AT HIGH SCHOOL LEVELS

The purposes of this qualitative descriptive study are (1) to describe the linguistic rules of the webtoon digital comic "Lucunya Hidup Ini", (2) to describe the implications of the webtoon digital comic "Lucunya Hidup Ini" as a medium for learning anecdotal texts at the high school level. The subject of this research is the digital comic Webtoon “Lucunnya Hidup Ini” episodes 20, 23,35, 42, 93, and 242.The object of this research is the linguistic elements of anecdotal texts in Webtoon digital comics and their implications as a medium for learning anecdotal texts. Methods of data collection in the form of note-taking methods and documentation methods. Data analysis techniques used are data reduction, data presentation, and drawing conclusions.The results show that (1) the digital comic Webtoon "Lucunya Hidup Ini" covering 6 episodes has found six linguistic elements of anecdotal texts contained in the form of past event sentences, rhetorical sentences, conjunctions, verbs, commands, and exclamations. This story is worthy of being used as a medium for learning anecdotal texts because it covers half of all linguistic elements of anecdotal texts. (2) The implication of using the webtoon digital comic "Lucunya Hidup Ini" as a medium for learning anecdotal texts at the high school level is very relevant to learning anecdotal texts because they contain the same linguistic elements. In addition, the “Lucunya Hidup Ini” Webtoon has the implication of triggering student interest in learning.

Terminological and conceptual apparatus of state legislation: international and national aspect

It is indicated that in legal science, the issue of the use of legal terminology, especially its unification, is considered as a problem of the language of domestic legislation. The problem of weak study of the language of legislation lies in the fact that lawyers drafting bills do not fully apply the rules of linguistics, and linguists probably do not devote enough time to researching the problems of legislative language as a special functional style of literary language, and also do not analyze legislative texts from a linguistic standpoint .It is determined that the development of the Ukrainian language, its functioning and improvement is directly related to the history of the formation of legal and socio-political institutions in close connection with the international practice of rulemakingand law enforcement. After February 24, 2022, due to the full-scale invasion of the russian federation on the territory of independent Ukraine and the need to restore territorial integrity as soon as possible, the Ukrainian language should beactively used in all spheres of public life. As for the political, administrative and legal spheres, this is a direct indication of the current legislation of Ukraine.In addition, in the context of ensuring the unity of the legal space in our country, we can state that legal terminology, as a completely open system, simultaneously includes both the terminology of international and domestic law, which makes theproblem of its unification particularly urgent, first of all, for the purpose of speeding up full membership of Ukraine in the EU. One of the ways to solve this problem, in our opinion, would be to compile dictionaries of modern legal terms with (interpretivebilingual or multilingual) the main purpose of which would be to provide practical assistance to specialists and researchers engaged in law enforcement activities both at the national and at international levels, work with international legal acts, teachers and students of universities, as well as a wide range of readers, since most of such terms (primarily we are talking about the terminological base in the field of human rights) belong to those legal terms that are most often used by people in everyday life and are common to people all over the world.

The Effect of Dialects on Triple Verb’s structures

The multiplicity and difference of ancient Arabic dialects have a significant impact on many of the linguistic rules established by Arab linguists, as each dialect had grammatical, morphological and phonetic phenomena that distinguish it from other ones. Although the morphological rules were built, like other linguistic rules, on the common majority of classical Arabic speech, there is an overlap in the structures of the triple verb sections, as a group of verbs came with different ratios to a specific section of the triple verb sections. The reason for this difference is mostly due to a difference in the pronunciation of these verbs. Their ratio, as such, is confused by the impact of the difference in the ancient Arabic dialects according to what the speakers of these tribes prefer. Another group remained trapped in individual use, preserved by linguists and included in their dictionaries and other works. Because of the importance of the topic, the research examines it in detail

Teaching and Learning Scientific Translation: Problems, Challenges, and Solutions

Scientific translation is not a kind of knowledge that could be gained by practice, or byimplementation of certain techniques. Therefore, teaching scientific translation does notinvolve the demonstration of its techniques and strategies only. However, it also involvesthe awareness of the requirements for this type of translation such as the expertise neededin this area, the consequences of neglecting linguistic and grammatical rules whentranslating scientific prose, the different barriers encountered, and the preliminary stepstaken before engaging in the translation. Similarly, learners of scientific translation shouldnot only learn the rules of scientific translation, but also be aware of the scientifictranslator’s job which is not the mere replacement of the source lexical terms with targetones. They should be learned that the translation of scientific prose, though non-literal,should render as directly as possible the exact meaning of the original. Accordingly, thispaper highlights the problems encountered when teaching and learning English-Arabicscientific translation. One of them is the students’ neglecting of the grammatical rules inscientific translation, which affects their translation of other text-types and influences andother modes of translation such as subtitling. The paper also attempts to offer solutionsand establish possible factors that may lead to a methodology of teaching and learning thistype of translation.

交互主观性视角下韩汉第一、二人称指示语的非常规用法

The theory of intersubjectivity has a strong explanatory power, which can be used to reinterpret and understand some linguistic phenomena, usages and rules in Korean and Chinese, especially some so-called marked usages. From the perspective of intersubjectivity, this paper focuses on the unconventional usage of first-person and second-person deixis in Korean and Chinese, including two aspects: the anti-pre-emptive usage between personal deictic pronouns and nominal components such as address terms, and the usage of pronoun dislocation between the deictic pronouns. The marked referential form has strong context dependence, which is not accidental, but the embodiment of the speaker''s communication strategies. We believe that intersubjectivity is the fundamental reason for the emergence or existence of this phenomenon. The unconventional usage of first-person and second-person deixis in Korean and Chinese has the discourse functions of “indirect pragmatic projection”, “stance marking function”, “alliance relationship construction”, “identity status representation”, “optimal relevance establishment”, “dynamic regulation of pragmatic distance”, “pragmatic ambivalence”, “communication viewpoint stance”. These discourse functions are the concrete manifestations of intersubjectivity. It can be said that the unconventional usage of the first-person and second-person deixis in Korean and Chinese is an expression with strong intersubjectivity.

ANALYSIS USE OF ELEMENTS, STRUCTURE, AND TEXT LANGUAGE RULES IN 2013 CURRICULUM

This research is motivated by the competencies that students must have in Indonesian language subjects, especially class VIII, namely understanding news texts, exposition texts, and poetry texts. In the 2013 curriculum, the material aims to enable students to convey their ideas and ideas logically and systematically in written form. This type of research is qualitative using descriptive method. The data in this study are excerpts of sentences or words contained in the students' texts, while the data sources used are the writings of these texts, students of class VIII SMP Pertiwi 2 Padang. The research instrument is the researcher himself and the data inventory format. The results of this study are summarized as follows.First, specifically for news texts, which use elements of only thirty-one student texts, and only twenty-five student texts use the language rules of news texts. Second, for the exposition text, which uses the structure of the exposition text, there are only twenty-six student texts, and fifteen student texts that use linguistic rules. Third, for poetry texts, there are only twenty-two student texts that use language rules.

Medical terminology-based computing system: a lightweight post-processing solution for out-of-vocabulary multi-word terms

The linguistic rules of medical terminology assist in gaining acquaintance with rare/complex clinical and biomedical terms. The medical language follows a Greek and Latin-inspired nomenclature. This nomenclature aids the stakeholders in simplifying the medical terms and gaining semantic familiarity. However, natural language processing models misrepresent rare and complex biomedical words. In this study, we present MedTCS—a lightweight, post-processing module—to simplify hybridized or compound terms into regular words using medical nomenclature. MedTCS enabled the word-based embedding models to achieve 100% coverage and enabled the BiowordVec model to achieve high correlation scores (0.641 and 0.603 in UMNSRS similarity and relatedness datasets, respectively) that significantly surpass the n-gram and sub-word approaches of FastText and BERT. In the downstream task of named entity recognition (NER), MedTCS enabled the latest clinical embedding model of FastText-OA-All-300d to improve the F1-score from 0.45 to 0.80 on the BC5CDR corpus and from 0.59 to 0.81 on the NCBI-Disease corpus, respectively. Similarly, in the drug indication classification task, our model was able to increase the coverage by 9% and the F1-score by 1%. Our results indicate that incorporating a medical terminology-based module provides distinctive contextual clues to enhance vocabulary as a post-processing step on pre-trained embeddings. We demonstrate that the proposed module enables the word embedding models to generate vectors of out-of-vocabulary words effectively. We expect that our study can be a stepping stone for the use of biomedical knowledge-driven resources in NLP.

ANALISIS KAIDAH KEBAHASAAN DALAM NOVEL SESUAP RASA KARYA CATZ LINK TRISTAN SEBAGAI ALTERNATIF PEMILIHAN BAHAN AJAR BAHASA INDONESIA KELAS XII

Learning about novels is an important lesson that must be mastered by students. However, in reality, students find it difficult to analyze novels because of a lack of understanding of the material. One of the reasons is the selection of Indonesian language teaching materials that are less attractive. Therefore, the author researched the linguistic rules of the novel so that it can be used as alternative teaching material. This study aims to analyze the linguistic rules in the novel Sesuap Rasa by Catz Link Tristan as a choice of Indonesian language teaching materials for class XII. The research method used is qualitative with data collection techniques, namely documentation, and literature study. The author uses data sources in the form of 61.53% of the number of pages in the novel. The results of the analysis show that 61.53% of the number of pages in the novel Sesuap Rasa by Catz Link Tristan contains 6 novel linguistic rules consisting of 471 adverbs of time, 1122 personal pronouns, 591 material verbs, 470 mental verbs, 517 adjectives. , and 979 dialogues. Based on the results of the study, the linguistic rules of the novel that have been analyzed can be used as teaching materials by the demands of the 2013 Curriculum. The results of the validation of Indonesian class XII teaching materials in the form of modules obtained an overall average score of 4.61 with a percentage of 92.2% included in the "Very Good" category.

Broad Learning Based Dynamic Fuzzy Inference System With Adaptive Structure and Interpretable Fuzzy Rules

This article investigates the feasibility of applying the broad learning system (BLS) to realize a novel Takagi–Sugeno–Kang (TSK) neuro-fuzzy model, namely a broad learning based dynamic fuzzy inference system (BL-DFIS). It not only improves the accuracy and interpretability of neuro-fuzzy models but also solves the challenging problem that models are incapable of determining the optimal architecture autonomously. BL-DFIS first accomplishes a TSK fuzzy system under the framework of BLS, in which an extreme learning machine auto-encoder is employed to obtain feature representation in a fast and analytical way, and an interpretable linguistic fuzzy rule is integrated into the enhancement node to ensure the high interpretability of the system. Meanwhile, the extended-enhancement unit is designed to achieve the first-order TSK fuzzy system. In addition, a dynamic incremental learning algorithm with internal pruning and updating mechanism is developed for the learning of BL-DFIS, which enables the system to automatically assemble the optimal structure to obtain a compact rule base and an excellent classification performance. Experiments on benchmark datasets demonstrate that the proposed BL-DFIS can achieve a better classification performance than some state-of-the-art nonfuzzy and neuro-fuzzy methods, simultaneously using the most parsimonious model structure.

The interpretability and scalability of linguistic-rule-based systems for solving regression problems

This study applies the idea of computing with words to develop an advanced genetic method to design the Linguistic Rule Base Systems (LRBSs) from a given dataset to solve the dataset regression problem, whose rules can be considered human knowledge. It has two primary specific features. The first is its ability to ensure the uncertain equality of two dataset contents assigned to each of its designed rules: the dataset content the users capture when reading it and the one the proposed method computes and assigns to it. Then, Tarski et al.'s interpretability concept in the math logics field does require the designed fuzzy sets to be isomorphic images of their assigned words. It implies their soundness in representing their words. The second is its ability to ensure the LRBs' scalability, an essential feature of human knowledge stating that it can grow while maintaining its existing one. Then, the proposed method can utilize the existing LRBSs optimality to design a new optimized LRBSs generation to increase the regression precision by allowing the existing L-attributes' word sets to grow. Compared to existing methods, the conducted experimental study can justify its performance and benefits in solving the regression problems using benchmark datasets in this area.

The Origin of Religious Tolerance and the Application of Pancasila

The main purpose of this article is to denote the historical fact that Piagam Jakarta does not only instruct the state to apply the Sharia for the Muslim population but it also softens the binding force of the Sharia by obligating the state to harmonize the requirements of Sharia with the comprehensive understanding of Pancasila in its entirety. The research finding: the historical fact indicates that the consent of the representatives of the Muslim group in Panitia Persiapan Kemerdekaan Indonesia (PPKI) as well as in Badan Penyelidik Usaha Persiapan Kemerdekaan Indonesia (BPUPKI) is to the abandonment of the Islamic Clause (klausula tentang Islam). They called for the deletion of any reference to Islam. Hence, for this research, it can be concluded that the Islamic Clause does not present a counter-draft but forms a preliminary stage of Pancasila and its first sila. This conclusion is also strengthened by linguistic rules referring to the word “Ketuhanan” abstaining from making any statement about the attitude of people towards God. Therefore, replacement of the Islamic Clause with the term “Ketuhanan Yang Maha Esa” has removed any boundary which would have been established by any religious doctrines against the inclusion of citizens with equal rights and has opened the way for Indonesia to implement the universal human rights to their full extend. The research is done through socio-legal approach. It sees historical data from socio-legal perspectives.

Aspect Based Sentiment Analysis of Unlabeled Reviews using Linguistic Rule Based LDA

In this digital era, people are very keen to share their feedback about any product, services, or current issues on social networks and other platforms. A fine analysis of these feedbacks can give a clear picture of what people think about a particular topic. This work proposed an almost unsupervised Aspect Based Sentiment Analysis approach for textual reviews. Latent Dirichlet Allocation, along with linguistic rules, is used for aspect extraction. Aspects are ranked based on their probability distribution values and then clustered into predefined categories using frequent terms with domain knowledge. SentiWordNet lexicon uses for sentiment scoring and classification. The experiment with two popular datasets shows the superiority of our strategy as compared to existing methods. It shows the 85% average accuracy when tested on manually labeled data.

LARQS: An Analogical Reasoning Evaluation Dataset for Legal Word Embedding

Applying natural language processing-related algorithms is currently a popular project in legal applications, for instance, document classification of legal documents, contract review and machine translation. Using the above machine learning algorithms, all need to encode the words in the document in the form of vectors. The word embedding model is a modern distributed word representation approach and the most common unsupervised word encoding method. It facilitates subjecting other algorithms and subsequently performing the downstream tasks of natural language processing vis-à-vis. The most common and practical approach of accuracy evaluation with the word embedding model uses a benchmark set with linguistic rules or the relationship between words to perform analogy reasoning via algebraic calculation. This paper proposes establishing a 1,256 Legal Analogical Reasoning Questions Set (LARQS) from the 2,388 Chinese Codex corpus using five kinds of legal relations, which are then used to evaluate the accuracy of the Chinese word embedding model. Moreover, we discovered that legal relations might be ubiquitous in the word embedding model.

Problematization of the phenomenon of social wellbeing

The article provides an review of problematization of social wellbeing. The author highlights the approaches to substantiating the definition of a phenomenon in various branches of knowledge based on the historical method and proposes to apply an interdisciplinary approach based on a divergent vision of the phenomenon as be the most relevant in the modern context of the socio-economic development of society. An important research aspect is the linguistic and semantic analysis of those forms that are used for the semantic expression of the phenomenon. The conceptualization of reality by an individual takes place with the help of the language and linguistic rules that are characteristic of certain societies. At the same time, the author outlines the difference between that the phenomena of wellbeing per se and social wellbeing. The paper also highlights the existential and meaning-forming aspect of social wellbeing. According to the author, the phenomenon of social wellbeing is a reflection of the cognitive movement of the individual and society on the way to the axiological reflection of the socio-cultural being of the individual. Herewith, constant transformation and changes in comprehension are possible, which may conflict with the accumulated experience or even ignore it.

A Linguistic Error Analysis of Google Translate Translation Result From Bahasa Indonesia To English

This study discusses the analysis of linguistic errors resulting from the translation of Indonesian text into English using Google Translate. The linguistic errors in question are errors at the morphological, syntactic, and semantic levels. The purpose of this research is to present the results of the analysis of linguistic errors in the translation of Indonesian texts into English and to describe examples of linguistic errors, with the hope that the use of Google Translate can provide complete and acceptable translation results in accordance with linguistic rules. The method used in this study is a descriptive qualitative method in which the researcher analyses linguistic errors in the Indonesian text which is translated into English. The subject of this research involved 13 students from the English Education Study Program at the Faculty of Teacher Training and Education, Pohuwato University. Research findings show that there are two linguistic errors found, which are classified into syntactic and morphological errors.

A Neuro-Fuzzy Approach to MOPP Open Time Prediction for Chemical Threats in Low-Intensity Conflicts

Chemical, Biological, Radiological and Nuclear (CBRN) weapon systems hold the potential to cause great damage to a fighting unit. Chemical warfare agents are cheaper and easier to produce and deploy. Mission oriented protective posture (MOPP) equipment is used to isolate soldiers from the toxic environment . Sustained wearing of MOPP overgarments can put soldiers at the risk of dehydration and heat stress. A hierarchal adaptive neuro-fuzzy inference system (HANFIS) model is proposed to predict worst case MOPP open times for surfaces covered with chemical agent resistant coating (CARC) and sand. The model can provide decision support for commanders when determining MOPP open or unmasking time. From HANFIS simulation results it was concluded that the model can accurately predict MOPP open times according to data present in military field manuals, in a manner which is computationally efficient. and easy to interpret based on linguistic rules and most importantly, easy to customize.

Analisis Perubahan Makna Gairaigo Dalam Website Marisol

Gairaigo is a type of Japanese vocabulary that comes from a foreign language and then adapted to the Japanese linguistic rules. Along with its development, many gairaigo underwent language changes of meaning compared to its original meaning. This will make Japanese language learners confused because it can lead them to different perception and will result in misinterpretation about the gairaigo meaning. This study aims to describe the semantic change of gairaigo which derived from English on the Marisol website. The type of research is a qualitative research with descriptive method. The data collection technique used in this research is to use watch method and note-taking technique. The data analysis techniques used in this study are match method and determining element sorting technique. The data used in this study is gairaigo which has changed the meaning contained in the Marisol website. The data source is the Marisol website. The result of this study showed that there were 39 data that have semantic change (underwent changes of meaning), there are 14 data whose meanings change broadly, 24 data meanings change to narrow and 1 data have total change in meaning.