Function Words Research Articles

Prediction of Plant Ubiquitylation Proteins and Sites by Fusing Multiple Features

Introduction: Protein ubiquitylation is an important post-translational modification (PTM), which is considered to be one of the most important processes regulating cell function and various diseases. Therefore, accurate prediction of ubiquitylation proteins and their PTM sites is of great significance for the study of basic biological processes and the development of related drugs. Researchers have developed some large-scale computational methods to predict ubiquitylation sites, but there is still much room for improvement. Much of the research related to ubiquitylation is cross-species while the life pattern is diversified, and the prediction method always shows its specificity in practical application. This study just aims at the issue of plants and has constructed computational methods for identifying ubiquitylation protein and ubiquitylation sites. Method: In this work, we constructed two predictive models to identify plant ubiquitylation proteins and sites. First, in the ubiquitylation proteins prediction model, in order to better reflect protein sequence information and obtain better prediction results, the KNN scoring matrix model based on functional domain Gene Ontology (GO) annotation and word embedding model, i.e. Skip-Gram and Continuous Bag of Words (CBOW), are used to extract the features, and the light gradient boosting machine (LGBM) is selected as the ubiquitylation proteins prediction engine. Results: As a result, accuracy (ACC), Precision, recall rate (Recall), F1_score and AUC are respectively 85.12%, 80.96%, 72.80%, 76.37% and 0.9193 in the 10-fold cross-validations on independent dataset. In the ubiquitylation sites prediction model, Skip-Gram, CBOW and enhanced amino acid composition (EAAC) feature extraction codes were used to extract protein sequence fragment features, and the predicted results on training and independent test data have also achieved good performance. Conclusion: In a word, the comparison results demonstrate that our models have a decided advantage in predicting ubiquitylation proteins and sites, and it may provide useful insights for studying the mechanisms and modulation of ubiquitination pathways

A Contrastive Study of the Grammaticalization Between “Gan Jing” and “Clean” Based on Corpus

Based on corpus study, this paper makes a diachronic study of the grammaticalization process of the Chinese word “Gan Jing” and English word “clean”. The study shows that both “Gan Jing” and “clean” gradually lose their original meaning and change from a content word to a functional word. The mechanisms of the grammaticalization include reanalysis, analogy, semantic bleaching, metonymy and metaphor, as well as subjectivity. These changes can be attributed to the principle of economy. Though “Gan Jing” and “clean” share many similarities in grammaticalization path, mechanisms and motivations, the use frequency of them varies. The lowly grammaticalized form of “Gan Jing” is most used while the highly-intensified meaning of “clean” is used more widely.

Диалектные частицы башкирского языка: семантика и функции

This article is devoted to the functional-semantic description of particles of the Karaidel subdialect of the northwestern dialect of the Bashkir language. As examples, field materials and transcribed audio recordings of the author, collected during an expedition to the Karaidel region of the Republic of Bashkortostan in 2022, 2023, were used in order to study the current state of dialect and analyze the morphological indicators of speakers’oral speech of this area. During the processing of field materials, the frequent use of various particles in the speech of informants was revealed, which convey an emotional attitude towards the events, incidents, state and actions of a particular subject or object under discussion. A comparative study of dialect forms with particles of the literary (written) Bashkir language made it possible to classify them in a semantic aspect. Since in colloquial speech specific dialect particles complement the meaning of a particular lexeme and thus their main function is to express an additional semantic connotation of the word. Based on their origin, particles of the Karaidel subdialect can be divided into original ones, dating back to the ancient Turkic state, and borrowed ones, which entered the Bashkir spoken language from the Russian language during centuries-old language contacts. It is noteworthy that some dialect particles of vernacular are observed in other Turkic languages (Kypchak, Oguz, Karluk, Siberian, etc. groups) and are not the literary norm of the Bashkir language. In addition, the article briefly examines the centuries-old history of the study of particles of the Bashkir language. The academic grammatical tradition, dating back to antiquity, considers particles according to the following meanings, which we have supplemented with new dialect materials: 1. Interrogative particles -мы, -ме, -мо, -мө. These particles of the Bashkir language are always written together. 2. The restrictive particles ғына, генә, ҡына, кенә distinguish this or that object or subject from others and are written separately. 3. Particles of doubt ҙар, -ҙыр, -ҙер, conveying uncertain assumptions, inaccuracy regarding an ongoing event, action, phenomenon, object. It should be noted that in the dialects of the northwestern dialect of the Bashkir language, particles of uncertainty and assumptions have only three variants -ҙар, -ҙыр, -ҙер, in contrast to the literary 4-variant affixation: -ҙар, -ҙер, -лар, -лер, -дар, -дәр, -тар, -тәр. 4. The particles of request -сана, -сәнә, -сы, -се, -со, -сө, әле, expressing exhortation, appear with verbs in the form of the imperative mood. The first two forms are used very rarely; mainly in dialects, requests are expressed in forms in , -сы, -се, -со, -сө and әле. 5. Particles of confirmation with a tinge of surprise and annoyance, expressing the emotional state of the speaker: ҙабаса, ҙәбәсә, даса, дәсә, даса(уы), дәсә(үы), дабаса, дәбәсә, табаса, тәбәсә, лабаса. 6. Intensifying particles уҡ, үк, иң, ныҡ, ҙа, ҙә, да, дә, та, тә, ла, лә enhance the meaning of the information expressed. The constant use of particles with the interdental voiced consonant ҙа, ҙә, conveying additional semantic shades to certain parts of speech, is a specific feature of the Karaidel dialect of the northwestern dialect of the Bashkir language and is observed only in the Bashkir language among other Turkic languages. 7. The next specific function word of this dialect is the affirmative dialect particle ҡый, кей in the meaning ‘after all; So; Yes’. So, dialectal data of the Bashkir language can serve as valuable material for comparative historical studies of Turkic languages, since the dialects of the Bashkir language have morphological facts for comparison with the languages of both the Kipchak and Bulgar, Oguz, Karluk and Siberian groups. Moreover, the dialects of the Bashkir language have many features that distinguish this language from other Turkic languages, so dialect materials can be a source of some important data for clarifying a number of questions on the history of the Turkic languages.

The subjunctive alternation in Indian English

AbstractThe study at hand is an exploration of the alternation between the mandative subjunctive and its equivalent modal construction with the verb should in Indian English. The study complements the growing body of research on the morphosyntax of the variety and it enhances our understanding of the relatively under‐researched alternation. It adds a special focus on the short‐term diachronic development of the subjunctive alternation in Indian English by using data from the South Asian Varieties of English corpus and its 2020 update. The following research questions are being investigated in the paper: Which factors influence the alternation between subjunctive and should in Indian English; are there short‐term diachronic adjustments to the subjunctive paradigm? A multifactorial model was fitted on 508 extracted data points with the following predictors: lexical diversity, newspaper, word count, distance, gender, linking word, negation, subject number, subject person, time and trigger lemma. The results show minor diachronic adjustments and highlight well‐known predictors of the alternation like voice as important factors.

Structural Complexity in Adapted Reading Materials: A Study Based on the Amount of Information

AbstractMost of the previous studies focused on lexical and syntactic features in adapted texts while little attention has been paid to the structural complexity from the perspective of the amount of information. In this study, we intend to examine the differences in structural complexity in adapted texts from the perspective of the amount of information at the lexical and grammatical levels. We also aim to identify the lexical and grammatical features that contribute most to such differences. The data used in this study were reading texts from Newsela, that is, reading materials for English learners under the educational system of K‐12 in the United States. This study yields several findings of interest. First, the adapted texts differ in the structural complexity at both lexical and grammatical levels in terms of their amount of information. Second, the differences display a decreasing trend. That is, the differences become smaller when the level of the text increases. Third, function words and part‐of‐speech trigrams with a preposition(s) and/or a noun(s) contribute most to the differences. The findings provide significant implications for the adaptation of language materials such as reading texts and test materials.

Exploring Semanticity for Content and Function Word Distinction in Catalan

In the realm of linguistics, the concept of “semanticity” was recently introduced as a novel measure designed to study linguistic networks. In a given text, semanticity is defined as the ratio of the potential number of meanings associated with a word to the number of different words with which it is linguistically linked. This concept provides a quantitative indicator that reflects a word’s semantic complexity and its role in a language. In this pilot study, we applied the semanticity measure to the Catalan language, aiming to investigate its effectiveness in automatically distinguishing content words from function words. For this purpose, the measure of semanticity has been applied to a large corpus of texts written in Catalan. We show that the semanticity of words allows us to classify the word classes existing in Catalan in a simple way so that both the semantic and syntactic capacity of each word within a language can be integrated under this parameter. By means of this semanticity measure, it has been observed that adverbs behave like function words in Catalan. This approach offers a quantitative and objective tool for researchers and linguists to gain insights into the structure and dynamics of languages, contributing to a deeper understanding of their underlying principles. The application of semanticity to Catalan is a promising pilot study, with potential applications in other languages, which will allow progress to be made in the field of theoretical linguistics and contribute to the development of automated linguistic tools.

Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model.

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguisticmeaning.

The Relationship Between L2 Spanish Proficiency and Features of Written Lexical and Lexicogrammatical Use

Abstract Research has demonstrated that features of lexical and lexicogrammatical use are important predictors of productive second language (L2) proficiency (e.g. Kyle et al. 2018). While some features of lexical use have been studied with L2s other than English (e.g. Tracy-Ventura 2017), multivariate lexical and lexicogrammatical approaches in these L2s are rare. In this study, we extend the use of multivariate approaches to L2 Spanish writing. Our learner data included a subset of the CEDEL2 corpus (Lozano 2021), comprised of proficiency scores and 644 descriptive essays written in L2 Spanish by L1 English writers. Correlational analyses were conducted between proficiency scores and indices of lexical diversity (e.g. MTLD), mean word and bigram frequencies, and bigram strength of association (MI, delta). A final regression analysis accounted for 48.3 per cent of the variance in proficiency scores. Following previous L2 English writing research (e.g. Kyle et al. 2018; Monteiro et al. 2020), more proficient L2 Spanish writers tended to use a wider variety of lexical items, more strongly associated word combinations, and lexical items that are less frequent in corpora.

Horizontal mapping of time-related words in first and second language

The existence of a consistent horizontal spatial-conceptual mapping for words denoting time is a well-established phenomenon. For example, words related to the past or future (e.g., yesterday/tomorrow) facilitate respective leftward/rightward attentional shifts and responses, suggesting the visual-spatial grounding of temporal semantics, at least in the native language (L1). To examine whether similar horizontal bias also accompanies access to time-related words in a second language (L2), we tested 53 Russian-English (Experiment 1) and 48 German-English (Experiment 2) bilinguals, who classified randomly presented L1 and L2 time-related words as past- or future-related using left or right response keys. The predicted spatial congruency effect was registered in all tested languages and, furthermore, was positively associated with higher L2 proficiency in Experiment 2. Our findings (1) support the notion of horizontal spatial-conceptual mapping in diverse L1s, (2) demonstrate the existence of a similar spatial bias when processing temporal words in L2, and (3) show that the strength of time-space association in L2 may depend on individual L2 proficiency.

Implicit relational aspects of the therapeutic relationship in psychoanalytic treatments: an examination of linguistic style entrainment over time

Objective: In an attempt to operationalize an implicit aspect of the therapeutic relationship, this study assesses reciprocal linguistic style entrainment (rLSM) between the patient and therapist. rLSM is defined as the dynamic adjustment of function word usage to synchronize or to be in rhythm with another person as they change over time. Method: In this exploratory study, levels of rLSM per talk turn were analyzed for 540 sessions of 27 long-term psychoanalytic treatments in relation to treatment outcomes. Results: Within sessions, rLSM appeared to decrease by the end of sessions and followed a negative linear trajectory, βlinear = −0.0002, SE < .001, t = −13.04, p < .001. Between sessions, rLSM showed significant variability such that neither a linear, nor a quadratic, nor a cubic trend line fit the session-by-session change over treatment. On average, therapist talk turns had significantly lower rLSM than patient talk turns, while accounting for the nested nature of the data using multilevel models βSpeakerT = −0.033, SE = 0.009, t = −3.65, p < .001. Levels of rLSM did not relate to treatment outcome. Conclusion: Most of the rLSM variance was at the within-patient and within-session level. rLSM was no indicator of psychoanalytic treatment outcomes.

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.

A machine-based corpus optimization method for extracting domain-oriented technical words: an example of COVID-19 corpus data

Although natural language processing (NLP) refers to a process involving the development of algorithms or computational models that empower machines to understand, interpret, and generate human language, machines are still unable to fully grasp the meanings behind words. Specifically, they cannot assist humans in categorizing words with general or technical purposes without predefined standards or baselines. Empirically, prior researches have relied on inefficient manual tasks to exclude these words when extracting technical words (i.e., terminology or terms used within a specific field or domain of expertise) for obtaining domain information from the target corpus. Therefore, to enhance the efficiency of extracting domain-oriented technical words in corpus analysis, this paper proposes a machine-based corpus optimization method that compiles an advanced general-purpose word list (AGWL) to serve as the exclusion baseline for the machine to extract domain-oriented technical words. To validate the proposed method, this paper utilizes 52 COVID-19 research articles as the target corpus and an empirical example. After compared to traditional methods, the proposed method offers significant contributions: (1) it can automatically eliminate the most common function words in corpus data; (2) through a machine-driven process, it removes general-purpose words with high frequency and dispersion rates –57% of word types belonging to general-purpose words, constituting 90% of the total words in the target corpus. This results in 43% of word types representing domain-oriented technical words that makes up 10% of the total words in the target corpus are able to be extracted. This allows future researchers to focus exclusively on the remaining 43% of word types in the optimized word list (OWL), enhancing the efficiency of corpus analysis for extracting domain knowledge. (3) The proposed method establishes a set of standard operation procedure (SOP) that can be duplicated and generally applied to optimize any corpus data.

THE MAIN FEATURES OF THE PARTİCLES IN THE ENGLISH LANGUAGE

Summary. In grammar, a particle is a range of words that fall outside the traditional eight parts of speech – noun, verb, pronoun, adjective, preposition, adverb, interjection, conjunction, yet there is no doubt about its value in language. So, what is a particle in English? The best way to look at it is as a function word, or word that must be associated with another to give meaning. An example would be the ‘to’ in the verb ‘to run’. Although to can be used as a preposition, with verbs like to run, to love, or to talk, it acts as something called an infinitive marker, and it doesn’t really have any meaning on its own. The broad term for words like this is particle. In English, for example, the phrase "oh well" has no purpose in speech other than to convey a mood. The word 'up' would be a particle in the phrase to 'look up' (as in the phrase "look up this topic"), implying that one researches something, rather than literally gazing skywards. Many languages use particles, in varying amounts and for varying reasons. In Hindi, they may be used as honorifics, or to indicate emphasis or negation. Key words: habit, word, meaning, expression, sentence, infinitive, function

Language assessment in persons with aphasia early after thrombolysis: the utility of multilevel procedures of discourse analysis

ABSTRACT Background Clinical guidelines recommend the administration of intravenous recombinant tissue plasminogen activator thrombolytic treatment to persons who suffered ischemic stroke within 4,5 hours since onset. However, the available evidence on the potential improvement of language after thrombolysis is still scanty. Aims This study assessed the effect of thrombolytic treatment in language recovery in persons with stroke aphasia (PWA) comparing the efficacy of traditional language assessments and a multilevel procedure of discourse analysis applied to the Cookie Theft picture descriptions taken from the National Institute of Health Stroke Scale (NIHSS). Methods and procedures Fortyeight individuals participated in the study: sixteen PWA who received thrombolysis; sixteen PWA who did not receive it; sixteen healthy controls. The two groups of PWA were balanced in terms of age, education, gender, lateralization of the lesion, and stroke severity. They were administered the NIHSS and a bedside language assessment battery when entering the neurological clinic (T0) and after approximately 72 hours (T1). Their narrative discourse descriptions were analyzed with a multilevel procedure for discourse analysis. Outcomes and results The two groups of PWA had similar linguistic difficulties at T0 as reflected by comparable Composite Verbal Scores and performance on traditional linguistic bedside assessment (Aphasia PostStroke Acute Assessment test; Furlanis et al., 2018). Discourse analysis highlighted the presence of more omissions of function words and errors of cohesion in the PWA who would receive thrombolysis with respect to healthy controls and allowed for the identification, in both groups, of difficulties that could not be detected through a traditional assessment. At T1 the analyses showed the presence of improvements likely reflecting a generalized spontaneous recovery in both groups of PWA and a more specific recovery triggered by thrombolysis concerning the production of global coherence errors in treated patients only. An inspection of the gravity of the linguistic symptoms at the individual level revealed high interindividual variability in this early phase suggesting that thrombolysis reduced the severity of the impairment also in the production of informative words. Conclusions Thrombolysis reduces the gravity of some linguistic symptoms within a few hours after treatment. Multilevel procedures of discourse analysis can identify these subtle improvements.

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.

Surjectivity of word maps on special linear groups of degree 2

Let K be an algebraically closed field of characteristic p≥0. Assume F, F(1), F(2), and (F(1))p are the free group on n>1 generators, the first and second derived subgroups of F, and the subgroup of F(1) generated by all p-powers, respectively. In this paper, among other results, we show that for any word w∈F(1)∖F(2)(F(1))p, the corresponding word map w:∏nPSL2(K)→PSL2(K) is surjective. We show that the class of such words w contains, for instance, all (weakly) Engel words.

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.

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.

Beyond content: discriminatory power of function words in text type classification

Abstract Our work aims to evaluate the strength of the association between function words and several text types: novels, poems, academic articles, reviews, and blog posts, and the accuracy of their classification to these categories, through machine-learning and statistical methods. The principal conclusion is that the types of texts are distinguishable based only on the function words, either by vocabulary or vocabulary diversity. Such findings may impact the techniques of authorship attribution based on function words and text clustering techniques since some function words add information about the text types/genres, in addition to content words.

Through the compression glass: language complexity and the linguistic structure of compressed strings

Abstract Against the backdrop of the sociolinguistic-typological complexity debate which is all about measuring, comparing and explaining language complexity, this article investigates how Kolmogorov-based information theoretic complexity relates to linguistic structures. Specifically, the linguistic structure of text which has been compressed with the text compression algorithm gzip will be analysed. One implementation of Kolmogorov-based language complexity is the compression technique (Ehret, Katharina. 2021. An information-theoretic view on language complexity and register variation: Compressing naturalistic corpus data. Corpus Linguistics and Linguistic Theory (2). 383–410) which employs gzip to measure language complexity in naturalistic text samples. In order to determine what type of structures compression algorithms like gzip capture, and how these compressed strings relate to linguistically meaningful structures, gzip’s lexicon output is retrieved and subjected to an in-depth analysis. As a case study, the compression technique is applied to the English version of Lewis Carroll’s Alice’s Adventures in Wonderland and its lexicon output is extracted. The results show that gzip-like algorithms sometimes capture linguistically meaningful structures which coincide, for instance, with lexical words or suffixes. However, many compressed sequences are linguistically unintelligible or simply do not coincide with any linguistically meaningful structures. Compression algorithms like gzip thus crucially capture purely formal structural regularities. As a consequence, information theoretic complexity, in this context, is a linguistically agnostic, purely structural measure of regularity and redundancy in texts.