Content Words Research Articles

Interpreting the Nasib Kulo Song of Kemas Anwar Beck in Bebaso (Semiotics Study)

A song is composed of a series of tones that form a melody and support musical elements. It uses the tones of a human voice to beautifully and meaningfully express thoughts or feelings The combination of a song with a lively poem (text) can stir up a lot of emotions in the audience and have a major effect on their soul. This study aims to explore the emotions evoked by Kemas Anwar Beck’s lyrics for his song Nasib Kulo and how his experiences show up in using language and wordplay to give his lyrics a unique and appealing quality. The study focuses on analyzing the content of the song lyrics and interpreting their meaning in a qualitative descriptive manner. A semiotic theory is used to decipher the meaning of the lyrics that were penned in polite Palembang Alus language. Moreover, a musicology approach is also used to analyze the musical form. The results show that the song Nasib Kulo uses two types of symbols, namely, verbal meaning in the form of poetry or lyrics and non-verbal meaning in the form of song elements, that is, chord progression, melody, tempo, and dynamics. As a result of the creativity of the artist, the mindset of life conception and lifestyle are reflected in his artwork. In conclusion, the song Nasib Kulo that is written in Palembang Alus language is very influential for individuals and communities. Keywords: interpretation, Nasib Kulo song, semiotics, artists, Palembang Alus

A Corpus-Based Study on Cohesion Development in Writing by EFL Novices

This corpus-based study explored the development of cohesive devices in the writing of Chinese beginner learners of English as a foreign language (EFL) over a three-year span. Quantitative analysis utilizing the Tool for Automatic Analysis of Cohesion (TAACO) was conducted on a longitudinal learner corpus comprising over 500 exam essays. Lexical, syntactic, semantic, and discourse features were examined to identify reliable indices for tracking learners’ progressive mastery of cohesion. Results revealed that pronoun-related features, including pronoun density and repetition, significantly differed across year pairs and robustly predicted writing development. However, most lexical and connective indices showed ambiguous trajectories over time. The findings highlight the vital role of pronouns in building coherence for novice writers and underscore persistent difficulties in acquiring sophisticated content words and their collocations. This study contributes data-driven insights into the nonlinear processes and enduring challenges shaping EFL beginners’ cohesive competence. It demonstrates the value of computational tools and learner corpora in exploring discourse acquisition.

Enhancing ESL Education with AI: Innovations in Teaching Methods and Au-thentic Materials

This article explores the integration of Artificial Intelligence (AI) in English as a Sec-ond Language (ESL) education, focusing on innovative teaching methods and authen-tic materials. AI-powered gamification is discussed, highlighting the use of AI tools like ChatGPT to enhance the gamification of key terms and concepts in ESL educa-tion. The interactive and enjoyable nature of gamified learning, combined with AI-driven content curation, deepens student understanding, critical thinking skills, and retention. By personalizing the learning experience, AI tools cater to individual stu-dent needs, allowing for flexibility in difficulty and fostering a love for the subject. Reflection and self-assessment play a crucial role in solidifying knowledge and pro-moting deeper learning. The article also discusses the importance of authentic materials in ESL education, emphasizing the use of AI-driven content curation to select and organize relevant and meaningful language content. AI-powered tools can analyze vast amounts of data, un-derstand patterns, and make accurate predictions, enhancing the user experience and delivering content that is most relevant and valuable to each individual student. The integration of AI in ESL education offers numerous benefits, including increased engagement, improved retention and application of key terms and concepts, personal-ized learning experiences, and enhanced critical thinking skills. By embracing AI-powered gamification and content curation, educators can create dynamic, interactive, and engaging learning experiences that foster a love for language learning and pro-mote deeper understanding.

Validation of an elicited Imitation test as a measure of Korean language proficiency

This study presents a modified version of the Korean Elicited Imitation (EI) test, designed to resemble natural spoken language, and validates its reliability as a measure of proficiency. The study assesses the correlation between average test scores and Test of Proficiency in Korean (TOPIK) levels, examining score distributions among beginner, intermediate, and advanced learner groups. Using item response theory (IRT), the study explores the influence of four key facets—learners, items, raters, and constructs—on performance evaluation. An explanatory item response modeling (EIRM) analysis identified linguistic factors impacting the EI test’s performance. Notably, the study uncovered a robust positive correlation between EI test scores and TOPIK levels. Significant score disparities were observed between beginner and intermediate, as well as beginner and advanced, learner cohorts. An IRT-based exploration of each facet revealed that item difficulty was comparatively lower in contrast to learners’ commendable performance, and raters exhibited a high degree of scoring consistency. The EIRM analysis underscores the significance of variables such as the number of syllables, vocabulary score, and content word density in influencing test performance.

Video Summarization for Marathi Language

The Video Summarization Platform using Python Flask is a comprehensive tool designed to summarize Marathi and English videos while providing summaries in Hindi, Marathi, and English languages. Leveraging machine learning and natural language processing (NLP) techniques, this platform offers a sophisticated solution for efficiently extracting key information from videos. The platform begins by transcribing the audio content of the video into text using automatic speech recognition (ASR) technology. This transcription process ensures that the platform can accurately analyze and summarize the video's content. Next, the text is translated into the target languages, namely Hindi, Marathi, and English, enabling users from diverse linguistic backgrounds to access the summarized content. To generate concise and informative summaries, advanced NLP algorithm is applied. This algorithm analyze the transcribed text to identify the most significant phrases, sentences, and concepts. By considering factors such as keyword frequency, semantic relevance, and context, the platform effectively distils the video's content into digestible summaries. Additionally, machine learning models are employed to classify the type of video content. These models are trained on diverse datasets encompassing various video genres and topics. By recognizing patterns and features within the video content, the platform can accurately categorize videos into distinct types, such as news, interviews, tutorials, or entertainment. The platform's user interface, powered by Python Flask, offers a seamless experience for users to upload videos, select their preferred language for summarization, and receive concise summaries in their chosen languages. The intuitive design ensures accessibility and ease of use, catering to both novice and advanced users. Overall, the Video Summarization Platform serves as a valuable resource for individuals seeking efficient ways to consume multimedia content. Whether for educational, informational, or entertainment purposes, this platform empowers users to access summarized video content in multiple languages, facilitated by cutting-edge machine learning and NLP technologies. Key Words: Transcription, Marathi-speaking users, Marathi YouTube videos, video content, transcription, summary, translation, Natural Language Toolkit (NLTK), content comprehension, user interaction data, past summaries, recommendation

Peningkatan Aktivitas dan Hasil Belajar Melalui Picture And Picture Tematik IIID SDN 77 Kota Bengkulu

This study aims to increase the activity and student learning outcomes in thematic learning through the picture and picture learning model in class IIID SDN 77 Bengkulu City. This research is a Classroom Action Research (CAR). The subjects in this study were class IIID students at SDN 77 Bengkulu City for the 2023/2024 academic year. The number of students in class IIID, a total of 48 students with details of 29 male students and 19 female students. Data collection techniques using observation sheet techniques and test sheets. The data analysis technique used on the observation sheet, namely the average value formula and for learning outcomes uses the average value formula and the percentage of completeness of classical learning. The results showed that there was an increase in activity and student learning outcomes in Thematic learning. It was seen in cycle I that the average value of teacher activity was 26.5, increasing in cycle II with an average value of 34. In cycle I student activity the average value was 27.5 increased in the second cycle with an average value of 34. In the first cycle student learning outcomes of Indonesian language content with an average value of 70.31 with a percentage of 66.66% with a total of 32 students have a complete score. It increased in cycle II with an average score of 77.60 with a percentage of 85.41% with a total of 43 students having a complete score. In the SBdP cycle I learning content with an average score of 74.47 with a percentage of 79.16% with a total of 38 students having a complete score. It increased in cycle II with an average score of 80.20 with a percentage of 89.58% with a total of 43 students having a complete score. It can be concluded that through the picture and picture learning model can increase student learning activities and results in thematic learning class IIID SDN 77 Bengkulu City.

Creative Nursing: History and Future Directions.

This article traces the development of Creative Nursing from its origin in 1981 as a newsletter about Primary Nursing to its current position as a quarterly international, interdisciplinary, peer-reviewed, indexed, themed journal that continues to nurture novice authors, welcome international submissions, review articles that other journals won't consider, and address subjects that many journals avoid. Future directions include content in multiple languages, new author guidelines that invite submissions of research methods papers, moving beyond statistical significance based on p-value thresholds, asking authors to make explicit the implications for knowledge translation in their papers, and thinking creatively about how artificial intelligence can be leveraged for research, education, and practice.

Linguistic dissection of nursing handoffs: Implications for patient safety in varied-acuity hospital settings.

This study examines the intricate language and communication patterns of nurse-to-nurse handoffs across three units with varying patient acuity levels and nurse-patient ratios, seeking to identify linguistic factors that may affect the quality of information transfer and patient outcomes. A mixed-methods cross-sectional design. This study used the Nurse-to-Nurse Transition of Care Communication Model to explore the content and meaning of language in nursing handoffs within a large academic medical centre. Data were collected on three units through digital audio recordings of 20 handoffs between June and September 2022, which were transcribed and analysed using the Linguistic Inquiry Word Count programme. Trustworthiness was established by adhering to COREQ and STROBE guidelines for qualitative and quantitative research, respectively. Analysis revealed a preference for casual, narrative language across all units, with ICU nurses demonstrating a higher confidence and leadership in communication. Cognitive processes such as insight and causation were found to be underrepresented, indicating a potential area for miscommunication. Communication motives driven by affiliation were more pronounced in ICU settings, suggesting a strong collaborative nature. No significant differences were observed among the units post multiple testing adjustments. Speech dysfluencies were most pronounced in ICU handoffs, reflecting possible stress and cognitive overload. The study highlights the need for improved communication strategies such as interventions to enhance language clarity and incorporating technological tools into handoff processes to mitigate potential miscommunications and errors. The findings advance nursing science by highlighting the critical role of nuanced language in varied-acuity hospital settings and the necessity for structured nurse education in handoff communication and standardized handoff procedures. This study underscores the critical role of language in nurse-to-nurse handoffs. It calls for enhanced communication strategies, technology integration and training to reduce medical errors, improving patient outcomes in high-acuity hospital settings. Nurses only.

"Nolite te bastardes carborundorum": Corpus Stylistics and Language of Margaret Atwood's The Handmaid's Tale

This paper investigates the stylistic and linguistic characteristics of Margaret Atwood's The Handmaid's Tale, a novel of Canadian origin. Employing a corpus-based approach, the researcher aims to analyze its stylistic features in-depth, focusing on specific predetermined categories. Quantitative analysis was facilitated through WordSmith 8.0 software, enabling the identification of keywords in context, which serve as indicators of the linguistic style within the selected corpus. Results indicate that the novel employs simple language and concise sentence structures. Moreover, it demonstrates lexical diversity, encompassing various themes with a higher type-token ratio (TTR), indicative of a diverse vocabulary. Notably, there is a notable prevalence of first-person singular pronouns throughout the text. Regarding content word distribution, verbs are the most frequently utilized, followed by nouns, pronouns, adverbs, and adjectives—additionally, the analysis of keywords aids in uncovering stylistic and linguistic elements embedded within the text.

Development of main concept and core lexicon checklists for the original and modern Cookie Theft stimuli

ABSTRACT Purpose To improve the utility of the cookie theft stimuli by reporting normative control data on both original and modern cookie theft pictures for clinically feasible discourse analysis measures. Method Forty-five transcripts of original cookie theft descriptions by healthy controls were retrieved from the AphasiaBank database and 50 transcripts of modern cookie theft descriptions were contributed by Berube and colleagues. Following the procedure used by Richardson & Dalton (2016), checklists of main concepts produced by at least 33% of participants in each task were identified. Similarly, the Dalton & Richardson (2016) procedure was used to create core lexicon lists, defined as any lemma that was produced by 50% or more of the sample. Descriptive statistics are reported to support the appropriateness of the samples for use as normative data. Results Nine and 14 main concepts were identified for the original and modern cookie theft stimuli, respectively. Six main concepts appeared in both checklists, with unique concepts for each stimulus as well. The average main concept composite score for the original cookie theft was 17.4 (SD = 3.8) with scores ranging from 10/27 to 26/27. For modern cookie theft the average main concept composite score was 28 (SD = 7.6) with scores ranging from 12/42 to 40/42. Twenty-six and 42 lemmas exceeded the 50% cut-off and were identified for the original cookie theft and the modern cookie theft stimuli, respectively. Nineteen core lexicon items were shared across both lists and there were also unique items for each. Twelve function words and 14 content words were identified for the original cookie theft stimulus and participants produced on average 9 (SD = 1.7) function and 11 (SD = 1.8) content words. Twenty function words and 22 content words were identified for the modern cookie theft picture and participants produced on average 15 (SD = 3.3) function and 16 (SD = 3.1) content words. Conclusions The modern cookie theft stimulus elicited more main concepts and core lexicon items compared to the original cookie theft stimulus, which can be attributed to the instructions used with the modern stimulus and the new characters and actions. MCA and Corlex analyses are sensitive functional measures that can be clinically utilized to assess communication ability across clinical populations.

Prosodic Change in Breton: The Loss of Stressed Clitics1

AbstractMost dialects of Breton have largely penultimate stress, and are also said to exhibit stress on certain clitics when they precede monosyllabic content words. However, data suggest that this prosodic process may not be maintained consistently by modern Breton speakers. This study explores the nature of clitic stress in Breton and investigates its potential loss by examining the indefinite article, low numerals and the adverb re ‘too’ in three pre‐existing corpora: two linguistic atlases and a more recent online repository of Breton recordings. The findings show that the loss of stressed clitics is greater in south‐eastern Brittany, and more advanced for the indefinite article than for other contexts. It is suggested that this is due to the fact that the process does not occur with the definite article, and that the clitics are being reanalysed such that they have a less cohering relationship with their hosts. Given the unstable nature of Breton as an endangered language with a high proportion of older speakers, it is unclear whether this ongoing language change will continue along the same path, or if revitalisation is likely either to halt or accelerate it.

On Subtitle Translation of American TV Series from the Perspective of Functional Equivalence Theory

With the development of globalization and cross-cultural communication, more and more artistic works are introduced into the promising market, China, including film and television works, music and novels. Of which, American TV series have become one of the hottest subjects, which arose enthusiastic pursuit and discussions among Chinese. Compared with domestic TV series, it contains more exciting plots and beautiful background music. What’s more, the quality subtitle is an essential part of this introduction. Regarding the theory put forward by Roman Jacobson, the founder of Prague school, translation is divided into three categories: intralingual translation, interlingual translation and intersemiotic translation, and subtitle translation is kind of interlingual translation. It means an interpretation of source language by means of target language. For film and television works, subtitle acts as a bridge between source language and audiences of target language as well as playing the role of communication and transformation of original emotions and image, which is the best illustration of functional equivalence theory developed by Eugene Nida. Differentiate from traditional literary translation, subtitle translation has its own unique features despite its being an emerging field. It has spatial and time constraint and must reproduce the content of source language as accurately and elegantly as possible within the limited time, as a result, this paper intends to carry out a further study on subtitle translation and functional equivalence theory. In 2018, the American TV series Killing Eve created a fad at home and abroad and the successful subtitle translation definitely contribute to it. In my perspective, its subtitle translation can be considered the great illustration of the principles and requirements of functional equivalence theory, which is a best case to study. From the perspective of functional equivalence theory, the paper has potential to produce a better understanding of subtitle translation's classification, features and related study at home and abroad. Give priority to the role of functional equivalence theory played in subtitle translation so as to give a boost to its development.

Exploring Spanish writing abilities of children with developmental language disorder in expository texts.

Numerous studies have shown that children with developmental language disorder (DLD), in addition to oral language difficulties, exhibit impaired writing abilities. Their texts contain problems in grammar, organization, cohesion, and length of written output. However, most of these studies have been conducted with English speakers. English is characterized by complex phonological structure, opaque orthography, poor morphology and strict word order. The aim of this research is to observe the writing abilities of children with DLD in a language with simple phonological structure, transparent orthography, rich morphology and flexible word order like Spanish in the production of expository texts. Twenty-six children with DLD (mean age in months = 128.85) and 26 age-and sex-matched typically developing (TD) children (mean age in months = 124.61) wrote an expository text about their favorite animal. In order to analyze how the two groups plan and encode written texts, we looked at word frequency and sentence structure, grammatical complexity and lexical density, and omissions and errors. Compared to the TD group, the children with DLD omitted more content words; made more errors with functional words, verb conjugation and inflectional morphemes, and made a large number of spelling errors. Moreover, they wrote fewer words, fewer sentences, and less structurally and lexically complex texts. These results show that children with DLD who speak a transparent orthography language such as Spanish also have difficulties in most language areas when producing written texts. Our findings should be considered when planning and designing interventions.

Validity and reliability of the Turkish version of the transition of primiparas becoming mothers scale

BackgroundThe transition to motherhood is an important life event in a woman’s life and represents an important developmental process that brings physical, psychological and social changes to gain a new role. However, research on the transition to motherhood in Turkish society is scarce. There is a need for a comprehensive, practical and reliable tool to evaluate the transition to motherhood in primiparous mothers. This study evaluated the reliability and validity of the Turkish version of the Transition of Primiparous Becoming Mothers Scale (TMP-S) to evaluate the transition process of primiparous mothers to motherhood.MethodsThis methodological research was carried out in obstetrics and gynecology outpatient clinics, pediatric outpatient clinics, and family health centers of a hospital in Türkiye. The sample consisted of primiparous mothers of 0 to 6- month-old babies who visited clinics and family health centers for routine postnatal examinations (n ​​= 305). After evaluating the language equivalence and content validity of the scale, test-retest reliability, internal consistency and construct validity were examined. Factor analysis, Pearson’s correlation, retest reliability, and Cronbach’s alpha were employed to evaluate structural validity and reliability.ResultsThe final TPM-S had two dimensions with 25 items. Exploratory factor analysis revealed a two-factor solution, which accounted for 59.276% of the variance. Confirmatory factor analysis showed that the model fit of the two-factor model also reached a satisfactory model ft after modification. The comparative fit index was 0.894, the Tucker‒Lewis index was 0.882, and the root mean square error of approximation was 0.079. The content validity index of the scale ranged from 0.56 ~ 0.77. The Cronbach’s alpha coefficient was 0.93 for the total scale, and the test–retest reliability was 0.96.ConclusionsIt is a valid and reliable tool for evaluating the transition to motherhood among primiparous mothers of 0 to 6 month-old babies in Türkiye. Turkish researchers and healthcare professionals can routinely apply this measurement tool to primiparous mothers in the first six months after birth to evaluate their transition to motherhood.

EMPOWERING COMMUNITIES: ASSESSING THE EFFECTIVENESS OF PROGRAMS AND LISTENERSHIP OF COMMUNITY RADIO

Community radio has long been recognized as a powerful tool for empowering marginalized communities by providing them with a platform to voice their concerns, share their stories, and access essential information. Community radio (CR) is a third-tier media, together with broadcasting on public and privately owned radio. This research paper throws light on the listenership pattern of listeners of community radio, their program preferences and CR programs' effectiveness on listeners. A survey was conducted among listeners of ‘Radio Varsha’ which is situated in the Gopalganj district of Bihar for the purpose of data collection and analysis. This study employs a mixed-method approach, combining quantitative survey data and extracts of discussions held with stakeholders and listeners. The research discovered that programs are effective in generating awareness on various topics among listeners. The broadcast content in local languages and dialects was liked by the listeners, thus, leading to the effectiveness of the programs.

The Targetedness of English Schwa: Evidence from Schwa-Initial Minimal Pairs

Schwa in English shows a considerable amount of contextual variation, to the extent that previous work has proposed that it is acoustically targetless. Although the consensus of previous research seems to suggest that schwa is targeted, the sources of schwa’s contextual variation have yet to be fully explained. We explored a potential source of variation in English schwa, namely, whether schwa occurs in a content word (word-initial schwa, e.g., accompany) or is a function word (phrase-initial schwa, e.g., a company). We sought to determine whether English speakers distinguish word- and phrase-initial schwas in production, as well as whether word- and phrase-initial schwas differ in their level of targetedness. To elicit hyperarticulation of word- and phrase-initial schwas and thereby facilitate our ability to observe their targets, participants produced ambiguous and unambiguous word- and phrase-initial schwa pairs in neutral and biased sentence contexts. The first and second formant trajectories of the schwas were analyzed using growth curve analysis, allowing us to demonstrate that word-initial and phrase-initial schwas are both targeted and have different targets. Ultimately, our results suggest different underlying representations for schwas in function and content words.

Demand for TV content in a national language: The case of Kazakhstan

This study examines preferences in selecting television content, using a national television channel as a case study. The Russian language put a lot of pressure on the Kazakh language during the communist regime. Post-Kazakhstan’s independence, linguistic dynamics shifted as authorities began responding to the demands of the Kazakh-speaking population. The aim is to test the hypothesis regarding the increasing demand for native language content, supported by the analysis of TV program ratings. For hypothesis testing, we employed empirical data obtained through an investigation into the preferences of the Kazakh-speaking audience. A total of 300 residents in Astana, aged 20-70, were interviewed. The survey results elucidate the correlation between public events and the television audience’s preferences. Historical, complex, and comparative analyses were employed, utilizing empirical data derived from a television audience preference study. The examination of television projects and their scripts revealed that language format substantially influences content informativeness and viewership ratings. Findings highlight a correlation between major events and television audience preferences. Programs in the Kazakh language elicit a positive response from the country’s television audience, particularly when discussing engaging topics. Based on research, recommendations are offered for enhancing editorial policies on television channels, with an emphasis on incorporating more Kazakh-language projects to better cater to the growing demand.

Teachers’ Perceptions on Corrective Feedback in Task-based Language Teaching (TBLT) and Content and Language Integrated Learning (CLIL) Contexts in Bangladesh

The use of Task-based Language Teaching (TBLT) and Content and Language Integrated Learning (CLIL) approaches in English as Foreign Language (EFL) classrooms has recently gained special attention. In the context of Bangladesh, English for Academic Purposes, a contextualized TBLT module prepared jointly by British Council and University Grant Commission Bangladesh, was piloted in English for Specific Purposes (ESP) courses in private universities in Bangladesh. This study explores TBLT and CLIL teachers' perceptions regarding feedback and how the success of TBLT and CLIL relates to providing feedback to the students of a large English class at the tertiary level. A mixed-method research design was adopted, including a questionnaire(n=50) and Focus Group Discussions (FGDs) (n=10) as research instruments among the English teachers at different universities. The results indicated that the classroom teachers as research participants were positive about providing corrective feedback to learners’ tasks in TBLT and CLIL classes. The participating teachers suggest some feasible and plausible ways and strategies to provide effective feedback to the students of a large English class.

Lexical-Semantic Content, Not Syntactic Structure, Is the Main Contributor to ANN-Brain Similarity of fMRI Responses in the Language Network.

Representations from artificial neural network (ANN) language models have been shown to predict human brain activity in the language network. To understand what aspects of linguistic stimuli contribute to ANN-to-brain similarity, we used an fMRI data set of responses to n = 627 naturalistic English sentences (Pereira et al., 2018) and systematically manipulated the stimuli for which ANN representations were extracted. In particular, we (i) perturbed sentences' word order, (ii) removed different subsets of words, or (iii) replaced sentences with other sentences of varying semantic similarity. We found that the lexical-semantic content of the sentence (largely carried by content words) rather than the sentence's syntactic form (conveyed via word order or function words) is primarily responsible for the ANN-to-brain similarity. In follow-up analyses, we found that perturbation manipulations that adversely affect brain predictivity also lead to more divergent representations in the ANN's embedding space and decrease the ANN's ability to predict upcoming tokens in those stimuli. Further, results are robust as to whether the mapping model is trained on intact or perturbed stimuli and whether the ANN sentence representations are conditioned on the same linguistic context that humans saw. The critical result-that lexical-semantic content is the main contributor to the similarity between ANN representations and neural ones-aligns with the idea that the goal of the human language system is to extract meaning from linguistic strings. Finally, this work highlights the strength of systematic experimental manipulations for evaluating how close we are to accurate and generalizable models of the human language network.

Atoms as words: A novel approach to deciphering material properties using NLP-inspired machine learning on crystallographic information files (CIFs)

In condensed matter physics and materials science, predicting material properties necessitates understanding intricate many-body interactions. Conventional methods such as density functional theory and molecular dynamics often resort to simplifying approximations and are computationally expensive. Meanwhile, recent machine learning methods use handcrafted descriptors for material representation, which sometimes neglect vital crystallographic information and are often limited to single property prediction or a sub-class of crystal structures. In this study, we pioneer an unsupervised strategy, drawing inspiration from natural language processing to harness the underutilized potential of Crystallographic Information Files (CIFs). We conceptualize atoms and atomic positions within a crystallographic information file similarly to words in textual content. Using a Word2Vec-inspired technique, we produce atomic embeddings that capture intricate atomic relationships. Our model, CIFSemantics, trained on the extensive material project dataset, adeptly predicts 15 distinct material properties from the CIFs. Its performance rivals that of specialized models, marking a significant step forward in material property predictions.