Syntactic Structure Of Sentence Research Articles

Representation of Syntactic Structures with Coordinating Conjunctions and Homonymy

The paper discusses sentences with coordinating conjunctions and homonymy where it is hard or impossible to build feasible syntactic structures using well-known models – dependency-based parse trees, constituency-based parse trees, and syntactic groups model. We suggest an approach to represent syntactic structures of sentences with conjunctions. We present features which distinguish our approach from the models under investigation. The paper shows multiple ways of visualization of syntactic structures. We illustrate how homonymy influences parsing and give examples of lexical and syntactic homonymy. We show the need to represent homonymy explicitly and suggest an approach to homonymy representation in morphological and syntactic structures.

Expected sum of edge lengths in planar linearizations of trees

Dependency trees have proven to be a very successful model to represent the syntactic structure of sentences of human languages. In these structures, vertices are words and edges connect syntacticallydependent words. The tendency of these dependencies to be short has been demonstrated using random baselines for the sum of the lengths of the edges or their variants. A ubiquitous baseline is the expected sum in projective orderings (wherein edges do not cross and the root word of the sentence is not covered by any edge), that can be computed in time O(n). Here we focus on a weaker formal constraint, namely planarity. In the theoretical domain, we present a characterization of planarity that, given a sentence, yields either the number of planar permutations or an efficient algorithm to generate uniformly random planar permutations of the words. We also show the relationship between the expected sum in planar arrangements and the expected sum in projective arrangements. In the domain of applications, we derive a O(n)-time algorithm to calculate the expected value of the sum of edge lengths. We also apply this research to a parallel corpus and find that the gap between actual dependency distance and the random baseline reduces as the strength of the formal constraint on dependency structures increases, suggesting that formal constraints absorb part of the dependency distance minimization effect. Our research paves the way for replicating past research on dependency distance minimization using random planar linearizations as random baseline.

Pengembangan Parsing PCPATR Sebagai Preservasi Bahasa dan Sastra Banjar

Banjar Mantra is part of the Banjar language and literature in the form of words recited orally by certain people. Mantras are considered to have magical powers for supernatural powers and curses. This study aims to develop a sentence parsing device as a Language and Literature Preservation of Banjar using a sentence parsing application (parse PC-PATR). Parse PC-PATR is a sentence parsing application that will produce a pattern tree to represent the syntactic structure of sentences based on the Banjar language grammars. The problem in this research is that the mantra corpus uses the old genre of Banjarese language and literature. Words in the old genre are currently not widely used in communication by the Banjar people. On the other hand, the absorption of Arabic also presents its own problems. Finally, it is difficult to find the availability of experts who still preserve the Banjar mantra. This research used the ADDIE method with 20 Banjar mantras as test sentences and involved 3 committees of linguists as examiners. The research results showed that the naturalness of the test sentences was as low as 6%. The average parsing tree suitability percentage is 98%. This shows that the sentence parser is acceptable even though the naturalness of the test sentences is only 18% on average.

The acquisition of nominal gender agreement: praxeology analysis of Arabic second language text book “Silsilah Al-Lisaan”

PurposeAssessing whether a book is relevant or suitable for use in teaching materials is not an easy and haphazard matter, various methods and theories have been offered by researchers in studying this matter. Taking a study of the context of textbooks, researchers found the urgency that textbooks are a foundation for education, socialization and transmission of knowledge and its construction. Researchers offer another approach, namely by using praxeology as a study tool so that the goals of the textbooks previously intended are fulfilled.Design/methodology/approachThe researcher uses a qualitative approach through grounded theory. Grounded theory procedures are designed to develop a well-integrated set of concepts that provide a thorough theoretical explanation of the social phenomena under study. A grounded theory must explain as well as describe. It may also implicitly provide some degree of predictability, but only with respect to certain conditions (Corbin and Strauss, 1990). Document analysis in conducting this research study. Document analysis itself examines systematic procedures for reviewing or evaluating documents, both printed and electronic materials.FindingsTwo issues regarding gender acquisition have been investigated in L2 Arabic acquisition studies; the order in which L2 Arabic learners acquire certain grammatical features of the gender system and the effect of L1 on the acquisition of some grammatical features from L2 grammatical gender. Arabic has a two-gender system that classifies all nouns, animate and inanimate, as masculine or feminine. Verbs, nouns, adjectives, personal, demonstrative and relative pronouns related to nouns in the syntactic structure of sentences show gender agreement.Research limitations/implicationsIn practice, as a book intended for non-speakers, the book is presented using a general view of linguistic theory. In relation to the gender agreement, the presentation of the book begins and is inserted with the concepts of nouns and verbs. Returning to the praxeology context, First, The Know How (Praxis) explains practice (i.e. the tasks performed and the techniques used). Second, To Know Why or Knowledge (logos) which explains and justifies practice from a technological and theoretical point of view. Answering the first concept, the exercise presented in the book is a concept with three clusters explained at the beginning of the discussion. And the second concept, explained with a task design approach which includes word categorization by separating masculine and feminine word forms.Practical implicationsPractically, this research obtains perspectives studied from a textbook, namely the Arabic gender agreement is presented with various examples of noun contexts; textbook authors present book concepts in a particular way with regard to curriculum features and this task design affects student performance, and which approach is more effective for developing student understanding. Empirically, the material is in line with the formulation of competency standards for non-Arabic speakers in Indonesia.Originality/valueWith this computational search, the researcher found a novelty that was considered accurate by taking the praxeology context as a review in the analysis of non-speaking Arabic textbooks, especially in the year 2022 (last data collection in September) there has been no study on this context. So then, the researcher finds other interests in that praxeology can examine more broadly parts of the task of the contents of the book with the approach of relevant linguistic theories.

Hierarchical dual graph convolutional network for aspect-based sentiment analysis

Aspect-based sentiment analysis (ABSA) is a kind of fine-grained task that predicts sentiment polarities for the given aspects in a sentence. Recently, graph-based methods such as graph convolutional networks (GCNs), graph attention networks (GATs) and their extensions have been used to model the syntactic structures of sentences and have achieved promising results. However, these graph-based methods generally homogenize dependencies and result in the loss of syntactic information. In addition, models that use only syntax-based graph methods are unable to identify the sentiments in informal reviews. In this study, we propose a dependency feature-aware hierarchical dual-graph convolutional network (HD-GCN) model, which consists of two specifically designed GCNs for extracting syntactic and semantic information. Specifically, for semantic information extraction, we leverage a self-attention matrix to represent the correlations between nodes. For syntactic information, we design a dependency feature-aware GCN that adaptively learns the mappings of various dependencies in the adjacency matrix. Moreover, we stack the network into multiple layers, and each layer learns different relation matrices to better obtain different levels of linguistic features. Extensive experiments are conducted on the SemEval 2014 and Twitter datasets, and the obtained experimental results are superior to those of the state-of-the-art models on the ABSA task, proving the effectiveness of our model.

Intonation as Means of Logic-Emotional Expressiveness in Professional Actor’s Verbal Action

The aim of the article is to reveal the peculiar features of intonation as one of the most essential means of a professional actor’s logic-emotional expressiveness, as well as to define the specificity of logical intonation of an utterance in the context of verbal activity. The research methodology. The author has applied typological, systems methods and the method of functional analysis to analyse intonation in the context of verbal activity by a professional actor. The method of terminological analysis has been used to specify basic terms and definitions of the research. The method of cognitive analysis has enabled the extrapolation of theoretical foundations of linguistics to the theatrical art. Scientific novelty. The article presents the research of intonation as the main means of logic-emotional expressiveness in the context of a professional actor’s verbal activity. The author has analysed the functions of intonation, peculiar features of its components, such as logical and verbal stress, pauses, rising and falling tones, speech melody, voice timbre, tempo, as well as intonation constructions in the theatrical speech. Moreover, the author has described some types of utterances with different emotional shades in the context of selecting language means by an actor to make a character expressive/well-marked. Conclusions. Connotative and emotional-stylistic differences in an actor’s speech when in an image appear as a result of cooperation between sentence syntactic structure, the lexis, intonation patterns used and denotative relations in the context. Emotional verbal expressiveness of a professional actor is a result of a complex work at all language levels: lexical, syntactical, and prosodic. Using intonation an actor can express various character’s emotions such as surprise, elation, joy, sadness, fear, and anger. Logical intonation in the professional actor’s speech comprises speech melody, tempo, and timbre. It is an inseparable component of a speech act and a powerful tool of influence on the audience. The spectators can understand through intonation only a specific emotion the actor expresses during the character presentation. Mastering stage speech at the professional level means a thorough selection of intonation means according to their communicative and pragmatic potential in a specific dramaturgic piece. Taking into account the influence of intonation pattern of a character’s mother tongue is one the essential elements of selecting verbal means of an actor’s expressiveness in the process of creating an image.
 Key words: intonation, logical intonation, logic-emotional expressiveness, stage speech, professional actor.

Compositional Evaluation on Japanese Textual Entailment and Similarity

Abstract Natural Language Inference (NLI) and Semantic Textual Similarity (STS) are widely used benchmark tasks for compositional evaluation of pre-trained language models. Despite growing interest in linguistic universals, most NLI/STS studies have focused almost exclusively on English. In particular, there are no available multilingual NLI/STS datasets in Japanese, which is typologically different from English and can shed light on the currently controversial behavior of language models in matters such as sensitivity to word order and case particles. Against this background, we introduce JSICK, a Japanese NLI/STS dataset that was manually translated from the English dataset SICK. We also present a stress-test dataset for compositional inference, created by transforming syntactic structures of sentences in JSICK to investigate whether language models are sensitive to word order and case particles. We conduct baseline experiments on different pre-trained language models and compare the performance of multilingual models when applied to Japanese and other languages. The results of the stress-test experiments suggest that the current pre-trained language models are insensitive to word order and case marking.

Gated tree-structured RecurNN for Detecting Biomedical Event Trigger

It is critical to deeply mine semantic features for information extraction. Tree-structured model is a linguistically attractive option due to its linguistic representations of sentence syntactic structure. Tree-LSTM has been introduced to represent tree-structured network topologies for the syntactic properties. To alleviate the limitation of the Tree-LSTM, we work towards addressing the issue by developing gated mechanism variants for the tree-structured network. The gated mechanism is more complex and diverse for the tree-structured model. We apply Child-Sum Tree-LSTM and Child-Sum Tree-GRU for recognizing biomedical event triggers, and develop two new gated mechanism variants incorporating peephole connection and coupled mechanism into the tree-structured model. The experimental results showed the advantage of gated units. The Child-Sum Tree-LSTM achieved the best results among the gated tree-structured models, and the performance of variants is nearly the same as Child-Sum Tree-LSTM. However, Child-Sum Tree-GRU and Child-Sum Tree-coupled reach reduction in computation time.

ОСМИ ФОРУМ „БЪЛГАРСКА ГРАМАТИКА“ / EIGHT FORUM ON BULGARIAN GRAMMAR

The Eighth Forum on Bulgarian Grammar titled Predication, Predicates, Predicatives was held on 21 and 22 October 2021. The Forum was organised by the Institute for Bulgarian Language Prof. Lyubomir Andreychin at the Bulgarian Academy of Sciences and the Department of Bulgarian Language of the Faculty of Slavic Studies at Sofia University St. Kliment Ohridski. The forum was dedicated to the 90th anniversary of one of the most renowned Bulgarian linguists of our time – Prof. DSc Yordan Penchev Penchev. The Forum’s topic encompassed a broad range of theoretical and applied issues related to the lexical peculiarities, the semantic description and the classification of (selected classes of) predicates and predicatives, the description of grammatical categories involved in the realisation of predication, the study of the syntactic patterns of argument expression and the identification of relevant semantic and grammatical features. The main focus of the discussion was centred around (though not limited to) the following issues: • Lexical and semantic characterisation of various classes of predicates and predicatives • Approaches to the description of valency and argument selection • The expression of predication at the morphological level • Semantic and syntactic structure of sentences with predicates and predicatives • Description of semantic and grammatical constraints on subject, complement and adjunct realisation. Following the established tradition, the papers presented at the Forum are published in Balgarski ezik’s Supplement.

Improving Neural Machine Translation by Transferring Knowledge from Syntactic Constituent Alignment Learning

Statistical machine translation (SMT) models rely on word-, phrase-, and syntax-level alignments. But neural machine translation (NMT) models rarely explicitly learn the phrase- and syntax-level alignments. In this article, we propose to improve NMT by explicitly learning the bilingual syntactic constituent alignments. Specifically, we first utilize syntactic parsers to induce syntactic structures of sentences, and then we propose two ways to utilize the syntactic constituents in a perceptual (not adversarial) generator-discriminator training framework. One way is to use them to measure the alignment score of sentence-level training examples, and the other is to directly score the alignments of constituent-level examples generated with an algorithm based on word-level alignments from SMT. In our generator-discriminator framework, the discriminator is pre-trained to learn constituent alignments and distinguish the ground-truth translation from the fake ones, while the generative translation model is fine-tuned to receive the alignment knowledge and to generate translations that best approximate the true ones. Experiments and analysis show that the learned constituent alignments can help improve the translation results.

Preschool Children's Processing of Events during Verb Learning: Is the Focus on People (Faces) or Their Actions (Hands)?

Verbs are central to the syntactic structure of sentences, and, thus, important for learning one’s native language. This study examined how children visually inspect events as they hear, and do not hear, a new verb. Specifically, there is evidence that children may focus on the agent of the action or may prioritize attention to the action being performed; to date, little evidence is available. This study used an eye tracker to track 2-, 3-, and 4-year-olds’ looking to the agent (i.e., face) vs. action (i.e., hands) while viewing events linked to a new verb as well as distractor events. A Tobii X30 eye tracker recorded children’s fixations to AOIs (head/face and hands) as they watched three target events and two distractor events in different orders during the learning phase, and pointed to one of two events in two test trials. This was repeated for a second novel verb. Pointing results show that children in all age groups were able to learn and extend the new verbs to new events at test. Additionally, across age groups, when viewing target events, children increased their looking to the hands (where the action is taking place) as those trials progressed and decreased their looking to the agents’ face, which is less informative for learning a new verb’s meaning. In contrast, when viewing distractor events, children decreased their looking to hands over trials and maintained their attention to the face. In summary, children’s visual attention to agents’ faces and hands differed depending on whether the events cooccurred with the new verb. These results are important as this is the first study to show this pattern of visual attention during verb learning, and, thus, these results help reveal underlying attentional strategies children may use when learning verbs.

Prosodic phrasing and the emergence of phrase structure

AbstractTo clarify the role of prosodic phrasing in the emergence of phrase structure, it is necessary to be clear as to how syntactic phrasing relates to prosodic phrasing. The core proposal here is that a distinction must be made between two basic types of syntactic constructions; namely, syntactic configurations for which prosodic phrasing is part of the definition of the construction, and phrase structure proper, which is independent of prosodic phrasing. This distinction implies a somewhat more complex view of the interface between syntax and prosody than is currently widely assumed. Rather than conceiving of prosodic phrases as derivative of syntactic phrases, prosodic phrasing and syntactic phrase structure are seen here as alternative ways of relating words to each other, forming larger units from smaller ones. Against this background, the emergence of phrase structure is conceived of as the emancipation of syntax from prosodic scaffolding.

Experiences on the Improvement of Logic-Based Anaphora Resolution in English Texts

Anaphora resolution is a crucial task for information extraction. Syntax-based approaches are based on the syntactic structure of sentences. Knowledge-poor approaches aim at avoiding the need for further external resources or knowledge to carry out their task. This paper proposes a knowledge-poor, syntax-based approach to anaphora resolution in English texts. Our approach improves the traditional algorithm that is considered the standard baseline for comparison in the literature. Its most relevant contributions are in its ability to handle differently different kinds of anaphoras, and to disambiguate alternate associations using gender recognition of proper nouns. The former is obtained by refining the rules in the baseline algorithm, while the latter is obtained using a machine learning approach. Experimental results on a standard benchmark dataset used in the literature show that our approach can significantly improve the performance over the standard baseline algorithm used in the literature, and compares well also to the state-of-the-art algorithm that thoroughly exploits external knowledge. It is also efficient. Thus, we propose to use our algorithm as the new baseline in the literature.

A Self-Supervised Representation Learning of Sentence Structure for Authorship Attribution

The syntactic structure of sentences in a document substantially informs about its authorial writing style. Sentence representation learning has been widely explored in recent years and it has been shown that it improves the generalization of different downstream tasks across many domains. Even though utilizing probing methods in several studies suggests that these learned contextual representations implicitly encode some amount of syntax, explicit syntactic information further improves the performance of deep neural models in the domain of authorship attribution. These observations have motivated us to investigate the explicit representation learning of syntactic structure of sentences. In this article, we propose a self-supervised framework for learning structural representations of sentences. The self-supervised network contains two components; a lexical sub-network and a syntactic sub-network which take the sequence of words and their corresponding structural labels as the input, respectively. Due to the n -to-1 mapping of words to their structural labels, each word will be embedded into a vector representation which mainly carries structural information. We evaluate the learned structural representations of sentences using different probing tasks, and subsequently utilize them in the authorship attribution task. Our experimental results indicate that the structural embeddings significantly improve the classification tasks when concatenated with the existing pre-trained word embeddings.

Speech Patterns in Litigation Documents (Exemplified by Decrees)

The study focuses on speech patterns typically used in litigation documents issued at the stage of criminal proceeding initiation and pre-trial investigation, which belong to the genre of decree. It is stated that Russian Federation Criminal Procedure Code and most of the Comments to it lack any language requirements to the text organization in these litigation documents. The article is aimed at defining characteristics of the decree genre structure; in particular, lexical and grammatical means that are used in decree texts are equated to the language norms. Some most frequent cases of lexical compatibility violation within set expressions and cliché of litigation documents and their combinations are detected. The author adheres to the opinion that language norms violations may have legal consequences in qualifying offenses and their types. The analysis of syntactic structure of sentences reveals that there is no distinction in the linguistic category of event completeness, in the texts they are presented as hypothetical events. Several aspects of modality in decree texts are studied. The author lays down some requirements on composing a narrative part of the decree as a forensic genre, makes an assertion that it is time to formulate some firm linguistic criteria of decree documentation organization and indicate the consent on expediency of linguistic expertize.

Syntax Vector Learning Using Correspondence for Natural Language Understanding

Natural language understanding (NLU) is a core technique for implementing natural user interfaces. In this study, we propose a neural network architecture to learn syntax vector representation by employing the correspondence between texts and syntactic structures. For representing the syntactic structures of sentences, we used three methods: dependency trees, phrase structure trees, and part of speech tagging. A pretrained transformer is used to propose text-to-vector and syntax-to-vector projection approaches. The texts and syntactic structures are projected onto a common vector space, and the distances between the two vectors are minimized according to the correspondence property to learn the syntax representation. We conducted massive experiments to verify the effectiveness of the proposed methodology using Korean corpora, i.e., Weather, Navi, and Rest, and English corpora, i.e., the ATIS, SNIPS, Simulated Dialogue-Movie, Simulated Dialogue-Restaurant, and NLU-Evaluation datasets. Through the experiments, we concluded that our model is quite effective in capturing a syntactic representation and the learned syntax vector representations are useful.

Složenost rečenične strukture na nematernjem jeziku kod bilingvalne dece

Serbian and Slovak are related languages and both languages belong to the group of Slavic languages. It is important to point out that bilingualism can have a negative impact on children's education, especially when they are not equally exposed to the use of both languages, as is the case with Slovaks in the Republic of Serbia. The aim of this paper is to determine the complexity of the syntactic structure in the non - mother tongue in bilingual children whose mother tongue is Slovak. The sample of children included forty children aged 7 years. The research was conducted at the Elementary School "Ljudovit Stur" in Kisac, and at the Elementary School "Jozef Marchok Dragutin" in Glozan. The assessment instruments used were: "Speech-language production test" and a bilingual questionnaire. The results obtained in this research speak in favor of a more complex syntactic sentence structure in bilingual children in their mother tongue compared to their non-mother tongue. We can conclude that bilingualism as a phenomenon has a great influence on the development of language, and thus on syntactic development. Slow language development can often occur due to the complexity of acquiring two languages at the same time.

The nature of syntactic relations reflected by word order in sentences in the novels

The topicality of the problem investigated is caused by necessity of studying the syntactic system of languages which is in line with main trends in modern linguistics. The aim of the research is to study the nature of syntactic relations expressed by word order in sentences in speech of authors and characters in the work of the 20th century American writer J.D. Salinger ‘The Catcher in the Rye’ and the work of the 21st century American writer L. Groff ‘Fates and Furies’. The following objectives of the study contribute to the achievement of the aim: to consider the rules of word order in a sentence in English; to study the works devoted to the study of syntax of a sentence; to analyze the syntactic structure of sentences in authors’ and characters’ speech in the novels «The Catcher in the Rye» by J.D. Salinger and «Fates and Furies» by L. Groff.

Extending latent semantic analysis to manage its syntactic blindness

Natural Language Processing (NLP) is the sub-field of Artificial Intelligence that represents and analyses human language automatically. NLP has been employed in many applications, such as information retrieval, information processing and automated answer ranking. Semantic analysis focuses on understanding the meaning of text. Among other proposed approaches, Latent Semantic Analysis (LSA) is a widely used corpus-based approach that evaluates similarity of text based on the semantic relations among words. LSA has been applied successfully in diverse language systems for calculating the semantic similarity of texts. LSA ignores the structure of sentences, i.e., it suffers from a syntactic blindness problem. LSA fails to distinguish between sentences that contain semantically similar words but have opposite meanings. Disregarding sentence structure, LSA cannot differentiate between a sentence and a list of keywords. If the list and the sentence contain similar words, comparing them using LSA would lead to a high similarity score. In this paper, we propose xLSA, an extension of LSA that focuses on the syntactic structure of sentences to overcome the syntactic blindness problem of the original LSA approach. xLSA was tested on sentence pairs that contain similar words but have significantly different meaning. Our results showed that xLSA alleviates the syntactic blindness problem, providing more realistic semantic similarity scores.

Teaching Russian students to analyze the syntactic structure of sentences in modern Chinese (Mandarin)

The paper deals with methodological issues of teaching senior students of language universities to analyze the syntactic structure of sentences in modern Chinese at the phrase level. The technology of teaching Russian students to analyze the syntactic structure of sentences in modern Chinese is presented in the following stages: 1) theoretical explanation of the classification of phrases in modern Chinese and methods of mastering this phenomenon by students; 2) introduction to five different ways of syntactic analysis of sentences at the phrase level; 3) presentation of features of the analysis "from small to large"; 4) improvement of skills of independent analysis of offers by students using the specified method. Much attention is paid to the order of establishment of relations between lexical items in phrases, combined with each other semantically. At the same time, in the developed technology, it is recommended to analyze the group of subject and predicate separately, performing an analysis from right to left. When faced with more difficult cases - long complicated sentences, the authors recommend analyzing the sentence in both directions, both from left to right and from right to left. Russian translation is recommended when determining the type of a phrase in Chinese. It is recommended that you translate the phrase into Russian, set its type in Russian, and then make a conclusion about the type of this phrase based on the typology used in Chinese. The existing limitations of using this method are discussed. As the main method of analyzing the syntactic structure of Chinese sentences, the analysis "from small to large" is chosen as the most convenient in implementation and allows parsing long complicated sentences.