Text Corpus Research Articles

Research on the Training and Application Methods of a Lightweight Agricultural Domain-Specific Large Language Model Supporting Mandarin Chinese and Uyghur

In the field of Natural Language Processing (NLP), the lack of support for minority languages, especially Uyghur, the scarcity of Uyghur language corpora in the agricultural domain, and the lightweight nature of large language models remain prominent issues. This study proposes a method for constructing a bilingual (Uyghur and Chinese) lightweight specialized large language model for the agricultural domain. By utilizing a mixed training approach of Uyghur and Chinese, we extracted Chinese corpus text from agricultural-themed books in PDF format using OCR (Optical Character Recognition) technology, converted the Chinese text corpus into a Uyghur corpus using a rapid translation API, and constructed a bilingual mixed vocabulary. We applied the parameterized Transformer model algorithm to train the model for the agricultural domain in both Chinese and Uyghur. Furthermore, we introduced a context detection and fail-safe mechanism for the generated text. The constructed model possesses the ability to support bilingual reasoning in Uyghur and Chinese in the agricultural domain, with higher accuracy and a smaller size that requires less hardware. It (our work) addresses issues such as the scarcity of Uyghur corpora in the agricultural domain, mixed word segmentation and word vector modeling in Uyghur for widespread agricultural languages, model lightweighting and deployment, and the fragmentation of non-relevant texts during knowledge extraction from small-scale corpora. The lightweight design of the model reduces hardware requirements, facilitating deployment in resource-constrained environments. This advancement promotes agricultural intelligence, aids in the development of specific applications and minority languages (such as agriculture and Uyghur), and contributes to rural revitalization.

Multi-word expressions for Russian L2 learners: corpora-based selection with expert verification

The article describes the experience of creating a corpus-based list of the most relevant multi-word expressions for Russian L2 learners, distributed across the levels of the Common European Framework of Reference for Languages (CEFR) from A1 to C1. Modern linguistic and cognitive research shows that our speech is patterned and largely consists of stable segments. This fact is supported by the linguodidactic idea of teaching not isolated language units but their combinations of different nature. However, the selection and ranking of multi-word expressions based on language proficiency levels is constrained by the difficulty of automatically extracting them from a corpus of texts and estimating their frequency, as well as disagreements in defining the boundaries, linguistic nature, and terminology of multi-word expressions. This article describes the experience of compiling a list of the most valuable fixed-type multi-word expressions from various sources: two types of existing CEFR-graded vocabulary lists for Russian L2 learners – lexical minimums for the TORFL (Test of Russian as a Foreign Language) system and Russian KELLY (KEywords for Language Learning for Young and adults alike); the most frequent n-grams from the RuFoLa – Russian L2 textbook corpus and from the Russian Web corpus of internet texts; list of discourse formulas from the «Pragmaticon» project. The CEFR level of each multi-word expression is predicted using the frequency-based Max Delta measure, and its effectiveness is subsequently validated through annotation by multiple experts. The resulting list of multi-word expressions contains 1645 entries from A1 to C1 levels. The proposed version of the list has been implemented into an automated text analysis system for learners of Russian as a Foreign Language and can be useful for a wide range of professionals in the preparation of educational content for foreign language learners. The suggested Max Delta measure has demonstrated a high degree of agreement with expert evaluations within proficiency levels A1-B1. This signifies the importance of further exploring its potential in addressing related practical tasks and in selecting language learning content derived for other languages.

“... but be sure you let it settle”: Late Modern Authors’ Presence in English Scientific Texts

The use of pronouns shows the author’s intention to address the reading public or the presence of the target readership in texts. This paper focuses on second-person pronouns, which are especially revealing of the author`s desire to engage the reader by endowing on them an active role in the negotiation and construction of knowledge. For the same reason, we will also analyse the use of the word reader. Science writing is thus understood as a dialogue between the two groups of participants involved in knowledge creation. Two usages of you have been detected in previous works using the Coruña Corpus of English Scientific Writing (CC): general and dialogic. The former might be interpreted as a generic “one,” “everybody;” the latter, considered as an in-group strategy that embraces both the writer and the reader. The detailed analysis of the pragmatics of the second person pronouns and reader in Corpus of English Chemistry Texts (CEChET) and Late Modern English Medical Texts (LMEMT) will hopefully shed some light on the object-centred nature of scientific writing.

Where and how machine learning plays a role in climate finance research

ABSTRACT The financial sector, by mobilizing capital, is fundamental to adapt and mitigate the impact of climate change in the economy. This has led to the emergence of a new research field, climate finance, where experts are starting to harness Machine Learning (ML) as a tool to solve new problems, due to the need to use big datasets and to model complex non-linear relationships. We propose a review of the academic literature that goes beyond the existing bibliometric studies in the field, with the aim of identifying relevant application domains of this technology to inform ML experts where and how their modeling expertise may add value in climate finance. To achieve this, we first assemble a corpus of texts from three scientific databases and use Latent Dirichlet Allocation (LDA) for topic modeling, to uncover seven research areas which we label as: natural hazards, biodiversity, agricultural risk, carbon markets, energy economics, Environmental, Social and Governance (ESG) factors & investing, and climate data. Second, we perform an analysis of publication trends, which confirms that ML is growing both in breadth and depth in climate finance, in particular topics related to energy economics, ESG factors and climate data. Interestingly, some methods stand out in each area, based on data characteristics and modeling requirements.

The Words for “Blue” in Old Frisian

Abstract The Old Frisian lexicon contains two words for ‘blue’: wēden, related to OE wǣden (MoE woaden arch.), OHG weitīn (MoG waiden arch.), and MLG wêden, with adjectival suffix *-īna stemming from PGmc *waida-, waidina- ‘woad, plant yielding blue dye’. The other one is blāw, a loanword through Middle Dutch or Middle Low German (from French), which is cognate with OE blǣhǣwen, OHG blāo, plāo, and ON blár, from PGmc *blēwa- < IE *bhel- ‘shining’ (cf. Lat. flavus ‘golden yellow’). This article analyses the occurrences of the words wēden and blāw in the Old Frisian text corpus in order to determine and contextualize the various semantic fields covered by these lexemes.

What do Contemporary Publications Report about the Generation of Urban Solid Waste (MSW) and/or Consumption from the Perspective of Chemistry Teaching?

The present study aimed to highlight the research on the topics of urban solid waste generation and consumerism from the perspective of Chemistry teaching between the years 2018 and 2023. To this end, a State-of-the-Art research, according to Romanowski and Ens (2006), in Periódicos Capes database on the aforementioned themes was realized. The methodology used was qualitative. The forms of analysis applied were both mediated by the IRAMuTeQ software and processed by the content analysis of Bardin (2002). In relation to the survey in Periódicos Capes, a textual corpus was obtained with 15 article summaries. Still as results, for textual statistics, the emergence of 82 text segments (ST) was observed, with the use of 65 ST (79.3%) and six classes in the Descending Hierarchical Classification (DHC). This is a satisfactory use and allows us to classify this analysis as consistent and consequently move on to content analysis based on the DHC. The mottos Waste and Generation were the highlights of the similarity analysis, preceded by the mottos Technology, Environmental, Student and Consumerism. In relation to content analysis, two very important categories emerged that communicate well with this object of study. As a consideration, it appears that in the contemporaneity of the last five years, there are strong signs of gaps regarding the use of these themes in the teaching of Chemistry, making it important for researchers to invest more time in the development of the area.

Fraseología dialectal en la obra literaria de B. Pérez Galdós

The prolific work of Benito Pérez Galdós is not, in general, characterised by the abundant presence of Canarian words and expressions. However, as Pérez Vidal (1979) and Corrales and Corbella (2020) point out, the conscious or unconscious use of lexical and phraseological items from the Archipelago can be traced in his literature. This paper analyzes and catalogs the dialectal phraseological units (PUs) extracted from a diachronic corpus of literary texts, compiled and managed by Sketch Engine. The main results of the study are the finding of a higher number of PUs than expected and the inclusion of Galdós’ dialectal phraseology in the research of the phraseological discipline from the postulates of diachronic linguistics.

Фонетические процессы в сочетаниях согласных (на материале осетинского языка)

The aim of the research is to identify all potential consonant clusters in the modern Ossetian literary language where assimilative and dissimilative changes are possible. The article discusses a detailed algorithm aimed at creating a theoretical basis for an orthoepic dictionary of the Ossetian literary language. The research is novel in that it is the first to obtain data on all possible assimilative and dissimilative processes in the Ossetian literary language. Consonant clusters were identified using a representative corpus of Ossetian texts presented on the Internet and consisting of 836,593 words. As a result of the study of 819 consonant clusters, such combinations were found in which, based on data on the phonemes of the Ossetian literary language, assimilative processes could be expected. In particular, this refers to consonant clusters where voiced and voiceless consonants meet at the boundaries of morphemes, voiced consonants in the final position and voiced consonants at the boundaries of morphemes. To determine the phonetic processes that occur in these clusters (progressive assimilation for voicing/devoicing, regressive assimilation for voicing/devoicing), words containing such clusters were included in the instrumental analysis program.

PERCEPTION OF SALVADOR DALí’S CREATION AND ITS INTERPRETATION IN THE TEXTS OF THE 20TH-21ST CENTURIES

The object of discourse is an extraordinary person with all his creations, which is constantly replenished by reviews of every subsequent generation of spectators revealing their attitude to the author and his works. The legacy of the great Spanish artist Salvador Dalí is a unique asset of the world artistic culture, which has come under scrutiny not only by his contemporaries, but also by a wide audience, art historians, scientists, film critics, literary scholars, poets and writers of the following generations. Due to the fact that the works of the great artist involve countless acts of interpretation and revision, and form an open space around the hitherto unsolved questions by the creator himself, the authors of the article proceed from the assumption that the discourse about Salvador Dali will continue to be enriched in the future cultural and historical context by the works of representatives of art and science. The present article focuses on the discourse about Salvador Dalí and his creations, which has been named the Dalinian discourse in the Spanish-language art tradition. The subject of the research are texts written by Dalí himself, his friends, and artists, as well as those written by the representatives of other sciences dwelling on the creations of the artist. The article attempts to systematise the main corpus of texts in Spanish about Dalí’s visual and literary work and to present its typology.

Navigating the Evolution of Game-Based Educational Approaches in Secondary STEM Education: A Decade of Innovations and Challenges

The need to support science, technology, engineering, and mathematics (STEM) learning in secondary education is reflected in the ongoing investigation of innovative pedagogical practices, including game-based learning (GBL). Using an analysis of scholarly publications based on word co-occurrence, this study aimed to identify the main research themes addressed in the past decade by the scholarly community on game-based teaching and learning solutions in the context of STEM education in secondary schools, their evolution over time, and the key issues addressed in recent years. After a systematic selection, the titles and abstracts of the publications were collected in a text corpus and analyzed using T-LAB software version 7.2.1.4 (2022). A preliminary visual exploration of the keywords was performed to obtain an overall view of the issues addressed by the research. Specificity analysis was then applied to identify, for each subset of the corpus identified by the years of publication, the evolution of themes reflected in a change in the frequency of lemma use. Finally, to explore the most recent topics, the main thematic clusters of publications in the last three years were identified (thematic analysis of elementary contexts). The results suggest some changes in the issues addressed over the past decade, such as a shift in focus from the specific technologies and competitive elements of games to understanding how GBL can support engagement, motivation, and understanding of complex scientific concepts. The five key thematic clusters identified (“Experience”, “Application”, “Validation”, “Emotion”, and “Programming”) also indicate a stronger emphasis by the latest publications on the experiential and emotional components of learning, the need for empirical studies, and the integration of computational thinking and coding into GBL. Overall, this study indicates that GBL has the potential to become an integrated component of STEM education, evolving with pedagogical and technological innovations.

Empirical application of sentiment analysis and emotions in Spanish: A post-cognitivist approach

Text mining has led to growth in sentiment analysis (SA) across various research disciplines. The pandemic has provided a unique and special context for analysing students’ written expression. We utilised comments from a survey conducted during the pandemic to create a corpus for SA. The corpus comprises 25,197 words extracted from over 600 comments in Spanish, collected during a survey that lasted around 20 days. We aim to detect sentiments and emotions from this corpus using SA. However, some essential and little-discussed issues in literature should be addressed, such as its relationship with post-cognitivist theory. This paper uses the post-cognitivist approach to analyse emotions and sentiments through SA with the Spanish lexicon in the economics of education. Literature in this area needs further development, especially in Spanish. The article shows that the emotions and sentiments of students in challenging situations can be identified through a corpus of student comments. However, specific elements should be considered while interpreting emotions and sentiments within the framework of post-cognitivism methodologies. Recognising that the human experience is a complex interaction, it is essential to consider the emotional nuances within the context in which they develop. Addressing this issue from the post-cognitivist approach is one of several ways to carry out this task. Using SA and emotions to analyse a text corpus is still helpful for researchers who follow the post-cognitivist approach. However, combining this technique with other qualitative and in-depth computational methods is essential to fully understanding the emotional experiences within their respective contexts.

Defending the “Backward Civilization”: The Resurrection of a Forgotten 17th Century Text in 20th Century Intellectual Discourse on Islam

It is an irony of history that since texts transcend the intentions and purposes of their authors, their meaning and significance are often contested anew as they enter new historical contexts; even historical texts are thus subject to reading and criticism over time. This article discusses the posthumous fate of Henry Stubbe’s own text on Islamic history, The Rise and Progress of Mahometanism—seen by some to represent a Copernican revolution in the study of Islam. The fate of this work is a clear example of the critical contingencies and fluctuating fortunes experienced by a corpus of texts. The continuing existence of a text as an object open to reconfiguration and re-evaluation is termed its after-history (Nachgeschichte) or afterlife (Nachleben). This notion of the afterlife of an object as a period of critical appreciation and political appropriation aptly defines the fate and fame of The Rise and Progress of Mahometanism. The present study seeks to explore the narrative surrounding a publication authored by Stubbe in the 17th century and finally published by Hafiz Mahmud Khan Shairani, with the critical support of Ottoman intellectual Halil Halid Bey, nearly two centuries later. Its objective is to investigate how the life and contributions of a figure whose work has transcended generations was resurrected within the political backdrop of the 20th century, as evidenced in the columns of Ottoman newspapers.

Social representations of health-disease-care, security, and food sovereignty of indigenous students from Insikiran

The social representations of Insikiran Indigenous students regarding health-illness, care, security, insecurity, and food sovereignty were analyzed, aiming for a contextualized understanding of these topics, which are scarcely explored in the literature. This case study employed an exploratory, descriptive, and qualitative approach and was conducted at the Insikiran Institute of Indigenous Higher Education. The methodology included processing the textual corpus formed by the responses of 22 Indigenous students, using SPSS and IRaMuTeQ software. The analyses encompassed descriptive statistics, lexical analysis, descending hierarchical classification, similarity analysis, and word cloud generation. The results highlighted significant thematic diversity, emphasizing the importance of traditional health practices, concerns with chronic diseases, and the relevance of food sovereignty. The social representations were organized into three main thematic groups, demonstrating the intersections between traditional and academic knowledge. This study underscores the importance of adopting interdisciplinary and culturally adapted approaches to promote health and well-being in Indigenous communities.

Wybory translatorskie XIX-wiecznego słownikarza rosyjskiego jako impuls do badań chronologizacyjnych polskiej leksyki zapożyczonej

Fifty-one entries (with the letter M) in the Russian-Polish dictionary of 1877 which were assigned a discussion of the meaning instead of a real translation, e.g. муссон – wjatr periodyczny [a periodic wind], were examined. These were limited to borrowed Russian units which today correspond to Polish borrowed units, e.g. муссон – monsun [monsoon]. The Polish words are the object of the analysis. In order to discover the reason for their omission from the dictionary, evidence of their use in the corpus of historical texts was sought. It was found that 80% of the borrowings (41 units) occurred in texts before 1876, but some of them were not recorded in the dictionaries of the time and perhaps that is why they did not find their way into the translation dictionary. 20% of the material (10 units) is lexis that entered circulation after the dictionary was published.

DAVOMLI HOZIRGI ZAMON GRAMMATIK SHAKLLARI ANNOTATSIYASI

The article provides information on the annotation and modeling of the grammatical forms representing the present continuous tense in the Uzbek language for the corpus. In this case, the existence of different situ- ations in their use in the text, the possibility of modeling these situations were analyzed. In the analysis, statistical indicators are based on the texts of the educational corpus of the Uzbek language (uzschoolcorpora.uz).

A materials terminology knowledge graph automatically constructed from text corpus

A scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation.

Challenges and prospects for teaching ocean literacy in Brazilian schools

This study took as a case study the perspective of teachers working in the State of Rio de Janeiro by 53 interviews to investigate the challenges and prospects of including content about the ocean in Brazilian school classrooms. The data were subjected to content analysis and explored quantitatively using Descending Hierarchical Classification (DHC) and Factor Correspondence Analysis (FCA) of word and terms used by teachers in their discourse. The main difficulties reported in including themes related to the ocean and marine environments in classes were the absence of OL in the school curriculum and university education, as well as the limited time to work on these subjects in classes, which is in line with the challenges faced by teachers from other countries. On the other hand, Brazilian teachers cited particular problems of Brazilian formal education, such as the need for professional development, support for an education with an interdisciplinary emphasis, and provision of financial resources for schools. However, DHC analysis also indicates strong connection of the teachers with the ocean due to sea fascination (24% of the answers in the textual corpus), spiritual and emotional connection (26.7%), leisure (22.7%) and professional interest (26.7%). Furthermore, the textual corpus also identified that teachers recognize the importance of teaching marine topics due to: students live in coastal areas (32.2%), the provision of ecosystem services (19.9%), preservation issues (34.2%), and limited student knowledge on these themes (13.7%). These data can help formulate educational policies to mitigate OL teaching barriers in Brazilian schools.

What should we call mental ill health? Historical shifts in the popularity of generic terms

Substantial attention has been paid to the language of mental ill health, but the generic terms used to refer to it–“mental illness”, “psychiatric condition”, “mental health problem” and so forth–have largely escaped empirical scrutiny. We examined changes in the prevalence of alternative terms in two large English language text corpora from 1940 to 2019. Twenty-four terms were studied, compounds of four adjectival expressions (“mental”, “mental health”, “psychiatric”, “psychological”) and six nouns (“condition”, “disease”, “disorder”, “disturbance”, “illness”, “problem”). Terms incorporating “condition”, “disease” and “disturbance” became less popular over time, whereas those involving “psychiatric”, “mental health” and “illness” became more popular. Although there were some trends away from terms with medical connotations and towards more normalizing expressions, “mental illness” consolidated its position as the dominant term over the study period.

An embedded diachronic sense change model with a case study from ancient Greek

Word meanings change over time, and word senses evolve, emerge or die out in the process. For ancient languages, where the corpora are often small and sparse, modelling such changes accurately proves challenging, and quantifying uncertainty in sense-change estimates consequently becomes important. GASC (Genre-Aware Semantic Change) and DiSC (Diachronic Sense Change) are existing generative models that have been used to analyse sense change for target words from an ancient Greek text corpus, using unsupervised learning without the help of any pre-training. These models represent the senses of a given target word such as “kosmos” (meaning decoration, order or world) as distributions over context words, and sense prevalence as a distribution over senses. The models are fitted using Markov Chain Monte Carlo (MCMC) methods to measure temporal changes in these representations. This paper introduces EDiSC, an Embedded DiSC model, which combines word embeddings with DiSC to provide superior model performance. It is shown empirically that EDiSC offers improved predictive accuracy, ground-truth recovery and uncertainty quantification, as well as better sampling efficiency and scalability properties with MCMC methods. The challenges of fitting these models are also discussed.

Conceptual Analysis through Corpus Text Patterns: Researching W.E.B. Du Bois’ Concept of Democratic Despotism via Regular Expressions

Conceptual Analysis through Corpus Text Patterns: Researching W.E.B. Du Bois’ Concept of Democratic Despotism via Regular Expressions