Kreuzer offers guidance to scholars looking to comparative historical analysis (CHA) for the tools to analyze macro-historical questions. Like history, CHA uses the past to formulate research questions, describe social transformations, and generate inductive insights. Like social science, CHA compares those patterns to explicate generalizable and testable theories. It operates in two different worlds—one constantly changing and full of cultural particularities and another static and full of orderly uniformities. CHA draws attention to the ontological constructions of these worlds; how scholars background historical and geographic particularities to create a social reality orderly enough for theorizing, while others foreground those particularities to re-complexify it to generate new inductive insights. CHA engages in ontological triage, dialogue between exploration and confirmation, and conversation in how to translate test results into genuine answers. This book is supplemented by online materials including introductory videos, diagnostic quizzes, advanced exercises, and annotated bibliographies.
Weixing Zhang, Jörg Holtmann, Daniel Strüber
et al.
In model-driven engineering, developing a textual domain-specific language (DSL) involves constructing a meta-model, which defines an underlying abstract syntax, and a grammar, which defines the concrete syntax for the DSL. Language workbenches such as Xtext allow the grammar to be automatically generated from the meta-model, yet the generated grammar usually needs to be manually optimized to improve its usability. When the meta-model changes during rapid prototyping or language evolution, it can become necessary to re-generate the grammar and optimize it again, causing repeated effort and potential for errors. In this paper, we present GrammarOptimizer, an approach for optimizing generated grammars in the context of meta-model-based language evolution. To reduce the effort for language engineers during rapid prototyping and language evolution, it offers a catalog of configurable grammar optimization rules. Once configured, these rules can be automatically applied and re-applied after future evolution steps, greatly reducing redundant manual effort. In addition, some of the supported optimizations can globally change the style of concrete syntax elements, further significantly reducing the effort for manual optimizations. The grammar optimization rules were extracted from a comparison of generated and existing, expert-created grammars, based on seven available DSLs.
We present and evaluate a method called grammar masking, which is used to guide large language models (LLMs) toward producing syntactically correct models for a given context-free grammar. Prompt engineering methods such as few-shot learning or priming can be used to improve the chances of an LLM producing correct syntax, but the more complex the grammar, the more time-consuming and less promising these methods become. Previous work is focused primarily on the usage of either language model training or prompt engineering. In this work, a method is presented that restricts the output to a given grammar using constrained decoding to ensure the output adheres to a valid syntax. We use several DSLs built with MontiCore and task multiple LLMs to produce models with and without constrained decoding. A corresponding parser is used to confirm the syntactic correctness of each model. We show that grammar masking can dramatically improve the modeling capabilities of several LLMs, reducing the need for well-refined prompting while increasing the chance of producing correct models.
Mohammad Rifat Arefin, Suraj Shetiya, Zili Wang
et al.
Black-box context-free grammar inference is a hard problem as in many practical settings it only has access to a limited number of example programs. The state-of-the-art approach Arvada heuristically generalizes grammar rules starting from flat parse trees and is non-deterministic to explore different generalization sequences. We observe that many of Arvada's generalization steps violate common language concept nesting rules. We thus propose to pre-structure input programs along these nesting rules, apply learnt rules recursively, and make black-box context-free grammar inference deterministic. The resulting TreeVada yielded faster runtime and higher-quality grammars in an empirical comparison. The TreeVada source code, scripts, evaluation parameters, and training data are open-source and publicly available (https://doi.org/10.6084/m9.figshare.23907738).
Kamran Akhtar Siddiqui, Rashid Hussain Abbasi, Ikramullah Khan
et al.
Reading and listening are two receptive skills indispensable for English language acquisition. Students are given reading and listening comprehension tests in academic settings, increasing the importance of these skills. However, reading and listening comprehension depends on various factors, including learning styles. While previous research in Pakistan has explored the connection between learning styles and academic success, there is a gap in the literature in understanding how specific learning styles, such as visual and auditory, influence fresh undergraduates' reading and listening comprehension. Therefore, employing a causal-comparative design under a quantitative paradigm, this study examined whether reading and listening comprehension differed based on their students' learning styles (visual and auditory). The data was collected using a learning style questionnaire, a reading comprehension test, and a listening comprehension test, and it was analyzed using an independent sample t-test. The findings revealed that students' reading and listening comprehension scores did not significantly differ based on their preferred learning styles, visual or auditory. The findings indicated that sig. values of reading comprehension (0.672) and listening comprehension (0.668) were greater than the p-value of 0.05. Hence, H0 was accepted, and Ha was rejected. The study will have implications for teachers who want to adapt their teaching methods to fit the individual learning styles of their students.
English literature, Language. Linguistic theory. Comparative grammar
Both Sender & Recipient do communicate through the utilization of signs within a specific context. These signs operate via Grammatical and Stylistic System, which has an essential role in testing meaning more accurately. As a matter of fact, in any communication based on Linguistic Interaction, errors can be corrected, words are modified, and even clarification could be increased. We usually raise inquiries, such as “Do you mean this?” The Recipient to this inquiry may clarify his idea by using more accurate style. But how do tags or signs function in a graphic speech? Can we consider these signs in a Caricature as the intended style? In order to answer these questions, we shall assume that the Semantic Interaction between the signs of a Caricature is the Style, and to test the validity of such assumption, we shall focus on the movement of signs towards the style and ending at the communication process, since the latter is deemed a critical point in testing meaning.
This paper analyses and compares the principles of linguistic categorisation of terms of venery in the Croatian and Russian languages. Since the monolingual and bilingual dictionaries of the Croatian and Russian languages do not exhaustively describe restrictions or criteria for the use of nouns that denote animals with terms of venery, a corpus study was conducted on the collocations of terms of venery, which aimed to determine more precisely how terms of venery classify groups of animals in the examined languages. In total, the paper analysed the use of 10 Croatian and 10 Russian terms of venery in the corpus of the Croatian language hrWaC and the corpus of the Russian language ruTenTen11 using the Sketch Engine tool. The sample was obtained by excerpting monolingual dictionaries of the Russian and Croatian languages. The similarities and differences in the classification of animal classes and the terms of venery used with each are schematically represented by four tables in the paper, which can serve as an aid when translating from one language to the other. The analysis showed that terms of venery do not categorise all groups of animals, but those that interact closely with humans. Etymological and historical lexicographical sources were used in the paper, with the goal of determining how the lexical combination of venery terms changed and to what extent the meaning of lexemes affects the principles of classification. Three naming models of terms of venery were singled out, namely: metonymic shift, types of animal movement, and the shape formed by a group of animals in motion. Some naming models are also classification criteria by which animals are divided. Terms of venery classify the animal world in both studied languages according to whether the animals are adults or young, according to the manner of moving, belonging to a particular (super)class of animals, and some quantifiers cover only one type of animal. Terms of venery cover the analysed categories of animal species in different ways in the Russian and Croatian languages, but the principles of organisation for the categories are very similar.
This paper uses computational experiments to explore the role of exposure in the emergence of construction grammars. While usage-based grammars are hypothesized to depend on a learner's exposure to actual language use, the mechanisms of such exposure have only been studied in a few constructions in isolation. This paper experiments with (i) the growth rate of the constructicon, (ii) the convergence rate of grammars exposed to independent registers, and (iii) the rate at which constructions are forgotten when they have not been recently observed. These experiments show that the lexicon grows more quickly than the grammar and that the growth rate of the grammar is not dependent on the growth rate of the lexicon. At the same time, register-specific grammars converge onto more similar constructions as the amount of exposure increases. This means that the influence of specific registers becomes less important as exposure increases. Finally, the rate at which constructions are forgotten when they have not been recently observed mirrors the growth rate of the constructicon. This paper thus presents a computational model of usage-based grammar that includes both the emergence and the unentrenchment of constructions.
The paper demonstrates the non-closure of the family of unambiguous linear languages (that is, those defined by unambiguous linear context-free grammars) under complementation. To be precise, a particular unambiguous linear grammar is presented, and it is proved that the complement of this language is not defined by any context-free grammar. This also constitutes an alternative proof for the result of Hibbard and Ullian ("The independence of inherent ambiguity from complementedness among context-free languages", J.ACM, 1966) on the non-closure of the unambiguous languages under complementation.
У статті розглянуто казкові прецедентні імена, дібрані із текстів англомовного медіа-дискурсу, на засадах когнітивної лінгвістики. Висвітлення лінгвокогнітивних особливостей казкових прецедентних імен здійснено у межах концептуального аналізу, що дало змогу виявити зв’язок між мовними і поняттєвими структурами.
Матерілом дослідження слугують цитовані висловлення, які містять казкові антропоніми, розміщені на інтернет-сайтах та у корпусі даних EnglishWeb 2020 (enTenTen20) додатку SketchEngine. Даний корпус – це англійський корпус текстів, зібраних з Інтернету в період з 2019 по 2021 рік. На основі аналізу зазначеного матеріалу запропоновано гіпотезу про те, що переважна частина казкових прецедентних імен, які функціонують у англомовному медіа-дискурсі, утворені за принципом аналогії. У дослідженні виявлено, що характерним для медійних текстів є вживання прецедентних імен у метафоричних моделях, за якими уподібнюються сутності, що належіть до різних понятійних сфер. При цьому порівняння об’єктів здійснюється за ознакою, спільною для обох порівнюваних сутностей. В аналізованому матеріалі метафора представлена моделями «ОСОБА-людина є начебто ТВАРИНА-міфонім» та «ОБ’ЄКТ-рослина є начебто ТВАРИНА-міфонім». У формуванні казкових прецедентних імен також використано принцип аналогії, визначальним для якої є порівняння двох сутностей, що належать до однієї понятійної сфери. Як правило, таке уподібнення компаратива (те, що порівнюють) та корелята (те, з чим порівнюють) відбувається за повним ступенем уподібнення. Здатність характеризувати інші предмети дійсності пояснюється в аспекті прототипності казкових прецедентних імен, а саме їх подібність, як зразкового представника класу, до провідної властивості первинного референта.
Результати дослідження показали, що частота аналогового порівняння (87,72%) казкових прецедентних імен на багато вища за метафоричне (12,28%), що підтверджує висунуту гіпотезу. Отже, можна зробити висновок, що у сучасному англомовному медіа-дискурсі казкові прецедентні імена утворені переважно на основі аналогії.
Ключові слова: казкові прецедентні імена, концептуальна метафора, когнітивна операція аналогового мапування, метод концептуального аналізу, прототип, англомовний медіа-дискурс.
Discourse analysis, Computational linguistics. Natural language processing
When working to understand usage of a data format, examples of the data format are often more representative than the format's specification. For example, two different applications might use very different JSON representations, or two PDF-writing applications might make use of very different areas of the PDF specification to realize the same rendered content. The complexity arising from these distinct origins can lead to large, difficult-to-understand attack surfaces, presenting a security concern when considering both exfiltration and data schizophrenia. Grammar inference can aid in describing the practical language generator behind examples of a data format. However, most grammar inference research focuses on natural language, not data formats, and fails to support crucial features such as type recursion. We propose a novel set of mechanisms for grammar inference, RL-GRIT, and apply them to understanding de facto data formats. After reviewing existing grammar inference solutions, it was determined that a new, more flexible scaffold could be found in Reinforcement Learning (RL). Within this work, we lay out the many algorithmic changes required to adapt RL from its traditional, sequential-time environment to the highly interdependent environment of parsing. The result is an algorithm which can demonstrably learn recursive control structures in simple data formats, and can extract meaningful structure from fragments of the PDF format. Whereas prior work in grammar inference focused on either regular languages or constituency parsing, we show that RL can be used to surpass the expressiveness of both classes, and offers a clear path to learning context-sensitive languages. The proposed algorithm can serve as a building block for understanding the ecosystems of de facto data formats.
This paper investigates two Turkish translations of fifteen short stories written by Ernest Hemingway. The first belongs to Yaşar Anday and it was published in 1972, and the second is a very recent translation, from 2017 by Elif Derviş. Derviş’s translation is the only Turkish translation that includes all Hemingway’s short stories. There are a number of challenges arising when the source language and the target language do not share the same or a similar cultural background. One of them is transferring the culture-specific elements. Eirlys E. Davies draws on Javier Franco Aixelá’s translation strategies for this type of items and creates a more flexible categorization. The strategies she proposes are: preservation, addition, omission, globalization, localization, transformation and creation. The significant time span between the two translations and their different cultural and social background resulted in quite different texts; nevertheless, they both preserve the foreign flavour of the original and the Turkish readers are well-aware that what they are reading is a translation.
Keywords: Translation, Culture, Hemingway, Turkish
This paper starts with an examination of the terms used to designate the face in different languages, in particular in Italian, comparing these with the definitions provided by some authoritative dictionaries as well as with their etymology. This exploration yields some remarkable results: firstly, it appears that the face is indeed a term that has a material meaning, but at the same time it is a social object; secondly, the importance of the communicative function emerges, which makes the face similar to the mask and in some ways to the arbitrariness of language. All this suggests that the philosophical status of the face is that of ‘transcendence’ which is a condition of that state of freedom that we attribute to ourselves and that can be defined as ‘human exception’.
This study asks whether translation might be a valid mode of (literary) criticism. It approaches a hortatory biblical text (1 Timothy 2.8-14 [3.1a]), somewhat notoriously and rigidly applied in some quarters of the church as containing timeless ethical instruction concerning women in the church, from the standpoint of its intertextual network, listening for resonance and dissonance as the relevant intertexts and precursor texts are explored. It is ultimately diagnosed as a text that is eschatologically obsolescent, and translated/rewritten, on the basis of its intertextual composition, to reflect the openness inscribed by the authorial Other.
Search, Structure or Statistics? A Comparative Study of Memoryless Heuristics for Syntax Acquisition William Gregory Sakas (sakas@hunter.cuny.edu) Department of Computer Science, Hunter College, CUNY Ph.D. Programs in Linguistics and Computer Science, The Graduate Center, CUNY 695 Park Avenue, New York, NY 10021 USA Eiji N ishimoto (enishimoto@gc.cuny.edu) Ph.D. Program in Linguistics, The Graduate Center, CUNY 365 Fifth Avenue, New York, NY 10016 USA Abstract Although several studies propose computational models of tlie process by which children acquire the syntax of their native language, most focus on a single algorithm applied in a single domain. Typically, the focus is learnability — under what conditions an algorithm can or cannot acquire the grammar of the target (native) language. Here, we present a comparative study of 12 algorithmic heuristics that are run in a domain that consists of 16 abstract languages each generated by a dijferent grammar specified in Chomsky’s principles and parameters fiamework. The heuristics consist of botl1 those used in previously established models and new variations that we introduce. In contrast to a leamability study, our focus is feasibility — how much time and/or eifort is required to achieve the target grammar. We find that the best heuristics make use of structural information obtained by parsing input sentences during the course of learning, that the performance of statistically- based heuristics are next in line, and finally, that heuristics that make use of hill-climbing search and a simple can-parse/can’t- parse outcome from the parsing mechanism perform least well. Background Principles and Parameters Chomsky (1981 and elsewhere) has proposed that all natural languages share the same innate universal principles (Universal Grammar - UG) and differ only with respect to the settings of a finite number of (binary) parameters. For example, all languages have a subject of some sort, but whether a language's grammar dictates that the subject must be overt is determined by the setting of the null subject parameter. The null subject parameter is set ofl ir1 English and on m Spanish. The syntactic component of a grammar m the principles and parameters (PP Briscoe, 2000; Clark, 1992; Fodor, 1998a; Gibson & Wexler, 1994; Yang, 2000; among others), and although it has proved linguistically fiuitfiil to construct parametric analyses, it turns out to be surprisingly difficult to construct a workable model of parametric syntax acquisition. Parametric Ambiguity and the Need for Heuristics A sentence is parametrically ambiguous if it is licensed by two or more distinct combinations of parameter values. Parametric ambiguity is rampant ir1 natural language. For example, a sequence of the form Subject-Verb-Object (SVO) is parametrically ambiguous between underlying SVO order as in English, and verb second (V2) order as m German.1 Although SVO sentences can be parsed by either grammar, the derivations will be different due to the different parameter settings. By contrast, a VOS sentence is not parametrically ambiguous with respect to the V2 parameter. It can be licensed only by the -V2 value (since the second token is not a verb or auxiliary). Ambiguity is a natural enemy of efficient language acquisition. The key problem is that, due to ambiguity, there does not exist a one-to-one correspondence between the linear left-to- right word order of an input sequence and the correct parameter values for the target grammar (as described above for an SVO sentence with respect to + or -V2). So, even if the learner hypothesizes parameter values which license the single, current input sentence, those values may ultimately be incorrect for Gag. In the face of parametric ambiguity, efficient search heuristics must be employed to guide the learner towards the target grammar as sentences are progressively consumed by the learner. The remainder of the paper presents a comparative study of 12 search heuristics that are incorporated into current parameter- setting models of language acquisition. Overview A Measure of Feasibility As a simple example of a learning heuristic and of our simulation approach, consider a domain of 4 parameters and a memoryless 1 See Appendix for the linguistic details of how we implement the V2 parameter.