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This thesis is a corpus linguistic investigation of the language used by young German speakers online, examining lexical, morphological, orthographic, and syntactic features and changes in language use over time. The study analyses the language in the Nottinghamer Korpus deutscher YouTube‐Sprache ("Nottingham corpus of German YouTube language", or NottDeuYTSch corpus), one of the first large corpora of German‐language comments taken from the videosharing website YouTube, and built specifically for this project. The metadatarich corpus comprises c.33 million tokens from more than 3 million comments posted underneath videos uploaded by mainstream German‐language youthorientated YouTube channels from 2008‐2018.
The NottDeuYTSch corpus was created to enable corpus linguistic approaches to studying digital German youth language (Jugendsprache), having identified the need for more specialised web corpora (see Barbaresi 2019). The methodology for compiling the corpus is described in detail in the thesis to facilitate future construction of web corpora. The thesis is situated at the intersection of Computer‐Mediated Communication (CMC) and youth language, which have been important areas of sociolinguistic scholarship since the 1980s, and explores what we can learn from a corpus‐driven, longitudinal approach to (online) youth language. To do so, the thesis uses corpus linguistic methods to analyse three main areas:
1. Lexical trends and the morphology of polysemous lexical items. For this purpose, the analysis focuses on geil, one of the most iconic and productive words in youth language, and presents a longitudinal analysis, demonstrating that usage of geil has decreased, and identifies lexical items that have emerged as potential replacements. Additionally, geil is used to analyse innovative morphological productiveness, demonstrating how different senses of geil are used as a base lexeme or affixoid in compounding and derivation.
2. Syntactic developments. The novel grammaticalization of several subordinating conjunctions into both coordinating conjunctions and discourse markers is examined. The investigation is supported by statistical analyses that demonstrate an increase in the use of non‐standard syntax over the timeframe of the corpus and compares the results with other corpora of written language.
3. Orthography and the metacommunicative features of digital writing. This analysis identifies orthographic features and strategies in the corpus, e.g. the repetition of certain emoji, and develops a holistic framework to study metacommunicative functions, such as the communication of illocutionary force, information structure, or the expression of identities. The framework unifies previous research that had focused on individual features, integrating a wide range of metacommunicative strategies within a single, robust system of analysis.
By using qualitative and computational analytical frameworks within corpus linguistic methods, the thesis identifies emergent linguistic features in digital youth language in German and sheds further light on lexical and morphosyntactic changes and trends in the language of young people over the period 2008‐2018. The study has also further developed and augmented existing analytical frameworks to widen the scope of their application to orthographic features associated with digital writing.
Song lyrics can be considered as a text genre that has features of both written and spoken discourse, and potentially provides extensive linguistic and cultural information to scientists from various disciplines. However, pop songs play a rather subordinate role in empirical language research so far - most likely due to the absence of scientifically valid and sustainable resources. The present paper introduces a multiply annotated corpus of German lyrics as a publicly available basis for multidisciplinary research. The resource contains three types of data for the investigation and evaluation of quite distinct phenomena: TEI-compliant song lyrics as primary data, linguistically and literary motivated annotations, and extralinguistic metadata. It promotes empirically/statistically grounded analyses of genre-specific features, systemic-structural correlations and tendencies in the texts of contemporary pop music. The corpus has been stratified into thematic and author-specific archives; the paper presents some basic descriptive statistics, as well as the public online frontend with its built-in evaluation forms and live visualisations.
This report presents a corpus of articulations recorded with Schlieren photography, a recording technique to visualize aeroflow dynamics for two purposes. First, as a means to investigate aerodynamic processes during speech production without any obstruction of the lips and the nose. Second, to provide material for lecturers of phonetics to illustrates these aerodynamic processes. Speech production was recorded with 10 kHz frame rate for statistical video analyses. Downsampled videos (500 Hz) were uplodad to a youtube channel for illustrative purposes. Preliminary analyses demonstrate potential in applying Schlieren photography in research.
In this paper, we will present a first attempt to classify commonly confused words in German by consulting their communicative functions in corpora. Although the use of so-called paronyms causes frequent uncertainties due to similarities in spelling, sound and semantics, up until now the phenomenon has attracted little attention either from the perspective of corpus linguistics or from cognitive linguistics. Existing investigations rely on structuralist models, which do not account for empirical evidence. Still, they have developed an elaborate model based on formal criteria, primarily on word formation (cf. Lăzărescu 1999). Looking from a corpus perspective, such classifications are incompatible with language in use and cognitive elements of misuse.
This article sketches first lexicological insights into a classification model as derived from semantic analyses of written communication. Firstly, a brief description of the project will be provided. Secondly, corpus-assisted paronym detection will be focused. Thirdly, in the main section the paper concerns the description of the datasets for paronym classification and the classification procedures. As a work in progress, new insights will continually be extended once spoken and CMC data are added to the investigations.
This paper presents a short insight into a new project at the "Institute for the German Language” (IDS) (Mannheim). It gives an insight into some basic ideas for a corpus-based dictionary of spoken German, which will be developed and compiled by the new project "The Lexicon of spoken German” (Lexik des gesprochenen Deutsch, LeGeDe). The work is based on the "Research and Teaching Corpus of Spoken German” (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK), which is implemented in the "Database for Spoken German” (Datenbank für Gesprochenes Deutsch, DGD). Both resources, the database and the corpus, have been developed at the IDS.
This paper presents the prototype of a lexicographic resource for spoken German in interaction, which was conceived within the framework of the LeGeDe-project (LeGeDe=Lexik des gesprochenen Deutsch). First of all, it summarizes the theoretical and methodological approaches that were used for the initial planning of the resource. The headword candidates were selected by analyzing corpus-based data. Therefore, the data of two corpora (written and spoken German) were compared with quantitative methods. The information that was gathered on the selected headword candidates can be assigned to two different sections: meanings and functions in interaction.
Additionally, two studies on the expectations of future users towards the resource were carried out. The results of these two studies were also taken into account in the development of the prototype. Focusing on the presentation of the resource’s content, the paper shows both the different lexicographical information in selected dictionary entries, and the information offered by the provided hyperlinks and external texts. As a conclusion, it summarizes the most important innovative aspects that were specifically developed for the implementation of such a resource.
In this paper, an exploratory data-driven method is presented that extracts word-types from diachronic corpora that have undergone the most pronounced change in frequency of occurrence in a given period of time. Combined with statistical methods from time series analysis, the method is able to find meaningful patterns and relationships in diachronic corpora, an idea that is still uncommon in linguistics. This indicates that the approach can facilitate an improved understanding of diachronic processes.
In this paper, a method for measuring synchronic corpus (dis-)similarity put forward by Kilgarriff (2001) is adapted and extended to identify trends and correlated changes in diachronic text data, using the Corpus of Historical American English (Davies 2010a) and the Google Ngram Corpora (Michel et al. 2010a). This paper shows that this fully data-driven method, which extracts word types that have undergone the most pronounced change in frequency in a given period of time, is computationally very cheap and that it allows interpretations of diachronic trends that are both intuitively plausible and motivated from the perspective of information theory. Furthermore, it demonstrates that the method is able to identify correlated linguistic changes and diachronic shifts that can be linked to historical events. Finally, it can help to improve diachronic POS tagging and complement existing NLP approaches. This indicates that the approach can facilitate an improved understanding of diachronic processes in language change.
We present a testsuite for POS tagging German web data. Our testsuite provides the original raw text as well as the gold tokenisations and is annotated for parts-of-speech. The testsuite includes a new dataset for German tweets, with a current size of 3,940 tokens. To increase the size of the data, we harmonised the annotations in already existing web corpora, based on the Stuttgart-Tübingen Tag Set. The current version of the corpus has an overall size of 48,344 tokens of web data, around half of it from Twitter. We also present experiments, showing how different experimental setups (training set size, additional out-of-domain training data, self-training) influence the accuracy of the taggers. All resources and models will be made publicly available to the research community.
One of the fundamental questions about human language is whether all languages are equally complex. Here, we approach this question from an information-theoretic perspective. We present a large scale quantitative cross-linguistic analysis of written language by training a language model on more than 6500 different documents as represented in 41 multilingual text collections consisting of ~ 3.5 billion words or ~ 9.0 billion characters and covering 2069 different languages that are spoken as a native language by more than 90% of the world population. We statistically infer the entropy of each language model as an index of what we call average prediction complexity. We compare complexity rankings across corpora and show that a language that tends to be more complex than another language in one corpus also tends to be more complex in another corpus. In addition, we show that speaker population size predicts entropy. We argue that both results constitute evidence against the equi-complexity hypothesis from an information-theoretic perspective.
We present a new resource for German causal language, with annotations in context for verbs, nouns and adpositions. Our dataset includes 4,390 annotated instances for more than 150 different triggers. The annotation scheme distinguishes three different types of causal events (CONSEQUENCE, MOTIVATION, PURPOSE). We also provide annotations for semantic roles, i.e. of the cause and effect for the causal event as well as the actor and affected party, if present. In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language. Finally, we present experiments where we frame causal annotation as a sequence labelling problem and report baseline results for the prediciton of causal arguments and for predicting different types of causation.
Classical null hypothesis significance tests are not appropriate in corpus linguistics, because the randomness assumption underlying these testing procedures is not fulfilled. Nevertheless, there are numerous scenarios where it would be beneficial to have some kind of test in order to judge the relevance of a result (e.g. a difference between two corpora) by answering the question whether the attribute of interest is pronounced enough to warrant the conclusion that it is substantial and not due to chance. In this paper, I outline such a test.
A syntax-based scheme for the annotation and segmentation of German spoken language interactions
(2018)
Unlike corpora of written language where segmentation can mainly be derived from orthographic punctuation marks, the basis for segmenting spoken language corpora is not predetermined by the primary data, but rather has to be established by the corpus compilers. This impedes consistent querying and visualization of such data. Several ways of segmenting have been proposed,
some of which are based on syntax. In this study, we developed and evaluated annotation and segmentation guidelines in reference to the topological field model for German. We can show that these guidelines are used consistently across annotators. We also investigated the influence of various interactional settings with a rather simple measure, the word-count per segment and unit-type. We observed that the word count and the distribution of each unit type differ in varying interactional settings and that our developed segmentation and annotation guidelines are used consistently across annotators. In conclusion, our syntax-based segmentations reflect interactional properties that are intrinsic to the social interactions that participants are involved in. This can be used for further analysis of social interaction and opens the possibility for automatic segmentation of transcripts.
We present an approach to an aspect of managing complex access scenarios to large and heterogeneous corpora that involves handling user queries that, intentionally or due to the complexity of the queried resource, target texts or annotations outside of the given user’s permissions. We first outline the overall architecture of the corpus analysis platform KorAP, devoting some attention to the way in which it handles multiple query languages, by implementing ISO CQLF (Corpus Query Lingua Franca), which in turn constitutes a component crucial for the functionality discussed here. Next, we look at query rewriting as it is used by KorAP and zoom in on one kind of this procedure, namely the rewriting of queries that is forced by data access restrictions.
In this paper, we present an overview of freely available web applications providing online access to spoken language corpora. We explore and discuss various solutions with which the corpus providers and corpus platform developers address the needs of researchers who are working with spoken language. The paper aims to contribute to the long-overdue exchange and discussion of methods and best practices in the design of online access to spoken language corpora.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).
In the first volume of Corpus Linguistics and Linguistic Theory, Gries (2005. Null-hypothesis significance testing of word frequencies: A follow-up on Kilgarriff. Corpus Linguistics and Linguistic Theory 1(2). doi:10.1515/ cllt.2005.1.2.277. http://www.degruyter.com/view/j/cllt.2005.1.issue-2/cllt.2005. 1.2.277/cllt.2005.1.2.277.xml: 285) asked whether corpus linguists should abandon null-hypothesis significance testing. In this paper, I want to revive this discussion by defending the argument that the assumptions that allow inferences about a given population – in this case about the studied languages – based on results observed in a sample – in this case a collection of naturally occurring language data – are not fulfilled. As a consequence, corpus linguists should indeed abandon null-hypothesis significance testing.
In the first volume of Corpus Linguistics and Linguistic Theory, Gries (2005. Null-hypothesis significance testing of word frequencies: A follow-up on Kilgarriff. Corpus Linguistics and Linguistic Theory 1(2). doi:10.1515/cllt.2005.1.2.277. http://www.degruyter.com/view//cllt.2005.1.issue-2/cllt.2005.1.2.277/cllt.2005.1.2.277.xml: 285) asked whether corpus linguists should abandon null-hypothesis significance testing. In this paper, I want to revive this discussion by defending the argument that the assumptions that allow inferences about a given population – in this case about the studied languages – based on results observed in a sample – in this case a collection of naturally occurring language data – are not fulfilled. As a consequence, corpus linguists should indeed abandon null-hypothesis significance testing.
Distributional models of word use constitute an indispensable tool in corpus based lexicological research for discovering paradigmatic relations and syntagmatic patterns (Belica et al. 2010). Recently, word embeddings (Mikolov et al. 2013) have revived the field by allowing to construct and analyze distributional models on very large corpora. This is accomplished by reducing the very high dimensionality of word cooccurrence contexts, the size of the vocabulary, to few dimensions, such as 100-200. However, word use and meaning can vary widely along dimensions such as domain, register, and time, and word embeddings tend to represent only the most prevalent meaning. In this paper we thus construct domain specific word embeddings to allow for systematically analyzing variations in word use. Moreover, we also demonstrate how to reconstruct domain specific co-occurrence contexts from the dense word embeddings.
This thesis consists of the following three papers that all have been published in international peer-reviewed journals:
Chapter 3: Koplenig, Alexander (2015c). The Impact of Lacking Metadata for the Measurement of Cultural and Linguistic Change Using the Google Ngram Data Sets—Reconstructing the Composition of the German Corpus in Times of WWII. Published in: Digital Scholarship in the Humanities. Oxford: Oxford University Press. [doi:10.1093/llc/fqv037]
Chapter 4: Koplenig, Alexander (2015b). Why the quantitative analysis of dia-chronic corpora that does not consider the temporal aspect of time-series can lead to wrong conclusions. Published in: Digital Scholarship in the Humanities. Oxford: Oxford University Press. [doi:10.1093/llc/fqv030]
Chapter 5: Koplenig, Alexander (2015a). Using the parameters of the Zipf–Mandelbrot law to measure diachronic lexical, syntactical and stylistic changes – a large-scale corpus analysis. Published in: Corpus Linguistics and Linguistic Theory. Berlin/Boston: de Gruyter. [doi:10.1515/cllt-2014-0049]
Chapter 1 introduces the topic by describing and discussing several basic concepts relevant to the statistical analysis of corpus linguistic data. Chapter 2 presents a method to analyze diachronic corpus data and a summary of the three publications. Chapters 3 to 5 each represent one of the three publications. All papers are printed in this thesis with the permission of the publishers.
This paper discusses computational linguistic methods for the semi-automatic analysis of modality interdependencies (the combination of complex resources such as speaking, writing, and visualizing; MID) in professional crosssituational interaction settings. The overall purpose of the approach is to develop models, methods, and a framework for the description and analysis of MID forms and functions. The paper describes work in progress—the development of an annotation framework that allows annotating different data and file formats at various levels, to relate annotation levels and entries independently of the given file format, and to visualize patterns.
As a consequence of a recent curation project, the Dortmund Chat Corpus is available in CLARIN-D research infrastructures for download and querying. In a legal expertise it had been recommended that standard measures of anonymisation be applied to the corpus before its republication. This paper reports about the anonymisation campaign that was conducted for the corpus. Anonymisation has been realised as categorisation, and the taxonomy of anonymisation categories applied is introduced and the method of applying it to the TEI files is demonstrated. The results of the anonymisation campaign as well as issues of quality assessment are discussed. Finally, pseudonymisation as an alternative to categorisation as a method of the anonymisation of CMC data is discussed, as well as possibilities of an automatisation of the process.
It is well known that the distribution of lexical and grammatical patterns is size- and register-sensitive (Biber 1986, and later publications). This fact alone presents a challenge to many corpus-oriented linguistic studies focusing on a single language. When it comes to cross-linguistic studies using corpora, the challenge becomes even greater due to the lack of high-quality multilingual corpora (Kupietz et al. 2020; Kupietz/Trawiński 2022), which are comparable with respect to the size and the register. That was the motivation for the creation of the European Reference Corpus EuReCo, an initiative started in 2013 at the Leibniz Institute for the German Language (IDS) together with several European partners (Kupietz et al. 2020). EuReCo is an emerging federated corpus, with large virtual comparable corpora across various languages and with an infrastructure supporting contrastive research. The core of the infrastructure is KorAP (Diewald et al. 2016), a scalable open-source platform supporting the analysis and visualisation of properties of texts annotated by multiple and potentially conflicting information layers, and supporting several corpus query languages. Until recently, EuReCo consisted of three monolingual subparts: the German Reference Corpus DeReKo (Kupietz et al. 2018), the Reference Corpus of Contemporary Romanian Language (Barbu Mititelu/Tufiş/Irimia 2018), and the Hungarian National Corpus (Váradi 2002). The goal of the present submission is twofold. On the one hand, it reports about the new component of EuReCo: a sample of the National Corpus of Polish (Przepiórkowski et al. 2010). On the other hand, it presents the results of a new pilot study using the newly extended EuReCo. This pilot study investigates selected Polish collocations involving light verbs and their prepositional / nominal complements (Fig. 1) and extends the collocation analyses of German, Romanian and Hungarian (Fig. 2) discussed in Kupietz/Trawiński (2022).
In this paper, we describe preliminary results from an ongoing experiment wherein we classify two large unstructured text corpora—a web corpus and a newspaper corpus—by topic domain (or subject area). Our primary goal is to develop a method that allows for the reliable annotation of large crawled web corpora with meta data required by many corpus linguists. We are especially interested in designing an annotation scheme whose categories are both intuitively interpretable by linguists and firmly rooted in the distribution of lexical material in the documents. Since we use data from a web corpus and a more traditional corpus, we also contribute to the important field of corpus comparison and corpus evaluation. Technically, we use (unsupervised) topic modeling to automatically induce topic distributions over gold standard corpora that were manually annotated for 13 coarse-grained topic domains. In a second step, we apply supervised machine learning to learn the manually annotated topic domains using the previously induced topics as features. We achieve around 70% accuracy in 10-fold cross validations. An analysis of the errors clearly indicates, however, that a revised classification scheme and larger gold standard corpora will likely lead to a substantial increase in accuracy.
In this paper we present the results of an automatic classification of Russian texts into three levels of difficulty. Our aim is to build a study corpus of Russian, in which a L2 student is able to select texts of a desired complexity. We are building on a pilot study, in which we classified Russian texts into two levels of difficulty. In the current paper, we apply the classification to an extended corpus of 577 labelled texts. The best-performing combination of features achieves an accuracy of 0,74 within at most one level difference.
Germany’s diverse history in the 20th century raises the question of how social upheavals were constituted in and through political discourse. By analysing basic concepts, the research network “The 20th century in basic concepts” (based at the Leibniz institutes IDS, ZfL, ZZF) aims to identify continuities and discontinuities in political and social discourse. In this way, historical sediments of the present are to be uncovered and those challenges identified that emerged in the course of the 20th century and continue to shape political discourse until the present.
Usenet is a large online resource containing user-generated messages (news articles) organised in discussion groups (newsgroups) which deal with a wide variety of different topics. We describe the download, conversion, and annotation of a comprehensive German news corpus for integration in DeReKo, the German Reference Corpus hosted at the Institut für Deutsche Sprache in Mannheim.
Enabling appropriate access to linguistic research data, both for many researchers and for innovative research applications, is a challenging task. In this chapter, we describe how we address this challenge in the context of the German Reference Corpus DeReKo and the corpus analysis platform KorAP. The core of our approach, which is based on and tightly integrated into the CLARIN infrastructure, is to offer access at different levels. The graduated access levels make it possible to find a low-loss compromise between the possibilities opened up and the costs incurred by users and providers for each individual use case, so that, viewed over many applications, the ratio between effort and results achieved can be effectively optimized. We also report on experiences with the current state of this approach.
Catching the common cause: extraction and annotation of causal relations and their participants
(2017)
In this paper, we present a simple, yet effective method for the automatic identification and extraction of causal relations from text, based on a large English-German parallel corpus. The goal of this effort is to create a lexical resource for German causal relations. The resource will consist of a lexicon that describes constructions that trigger causality as well as the participants of the causal event, and will be augmented by a corpus with annotated instances for each entry, that can be used as training data to develop a system for automatic classification of causal relations. Focusing on verbs, our method harvested a set of 100 different lexical triggers of causality, including support verb constructions. At the moment, our corpus includes over 1,000 annotated instances. The lexicon and the annotated data will be made available to the research community.
This contribution explores the relationship between the English CEFR (Common European Framework of Reference for Languages) vocabulary levels and user interest in English Wiktionary entries. User interest was operationalized through the number of views of these entries in Wikimedia server logs covering a period of four years (2019–2022). Our findings reveal a significant relationship between CEFR levels and user interest: entries classified at lower CEFR levels tend to attract more views, which suggests a greater user interest in more basic vocabulary. A multiple regression model controlling for other known or potential factors affecting interest: corpus frequency, polysemy, word prevalence, and age of acquisition confirmed that lower CEFR levels attract significantly more views even after taking into account the other predictors. These findings highlight the importance of CEFR levels in predicting which words users are likely to look up, with implications for lexicography and the development of language learning materials.
CLARIN contractual framework for sharing language data: the perspective of personal data protection
(2020)
The article analyses the responsibility for ensuring compliance with the General Data Protection Regulation (GDPR) in research settings. As a general rule, organisations are considered the data controller (responsible party for the GDPR compliance). Research constitutes a unique setting influenced by academic freedom. This raises the question of whether academics could be considered the controller as well. However, there are some court cases and policy documents on this issue. It is not settled yet. The analysis serves a preliminary analytical background for redesigning CLARIN contractual framework for sharing data.
We present web services which implement a workflow for transcripts of spoken language following the TEI guidelines, in particular ISO 24624:2016 “Language resource management – Transcription of spoken language”. The web services are available at our website and will be available via the CLARIN infrastructure, including the Virtual Language Observatory and WebLicht.
CLARIN, the "Common Language Resources and Technology Infrastructure", has established itself as a major player in the field of research infrastructures for the humanities. This volume provides a comprehensive overview of the organization, its members, its goals and its functioning, as well as of the tools and resources hosted by the infrastructure. The many contributors representing various fields, from computer science to law to psychology, analyse a wide range of topics, such as the technology behind the CLARIN infrastructure, the use of CLARIN resources in diverse research projects, the achievements of selected national CLARIN consortia, and the challenges that CLARIN has faced and will face in the future.
The book will be published in 2022, 10 years after the establishment of CLARIN as a European Research Infrastructure Consortium by the European Commission (Decision 2012/136/EU).
The paper presents best practices and results from projects dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC) from four different countries. Even though there are still many open issues related to building and annotating corpora of this type, there already exists a range of tested solutions which may serve as a starting point for a comprehensive discussion on how future standards for CMC corpora could (and should) be shaped like.
CMC Corpora in DeReKo
(2017)
We introduce three types of corpora of computer-mediated communication that have recently been compiled at the Institute for the German Language or curated from an external project and included in DeReKo, the German Reference Corpus, namely Wikipedia (discussion) corpora, the Usenet news corpus, and the Dortmund Chat Corpus. The data and corpora have been converted to I5, the TEI customization to represent texts in DeReKo, and are researchable via the web-based IDS corpus research interfaces and in the case of Wikipedia and chat also downloadable from the IDS repository and download server, respectively.
Since 2013 representatives of several French and German CMC corpus projects have developed three customizations of the TEI-P5 standard for text encoding in order to adapt the encoding schema and models provided by the TEI to the structural peculiarities of CMC discourse. Based on the three schema versions, a 4th version has been created which takes into account the experiences from encoding our corpora and which is specifically designed for the submission of a feature request to the TEI council. On our poster we would present the structure of this schema and its relations (commonalities and differences) to the previous schemas.
In this Paper, we describe a schema and models which have been developed for the representation of corpora of computer-mediated communicatin (CMC corpora) using the representation framework provided by the Text Encoding Initiative (TEI). We characterise CMC discourse as dialogic, sequentially organised interchange between humans and point out that many features of CMC are not adequately handled by current corpus encoding schemas and tools. We formulate desiderata for a representation of CMC in encoding schemes and argue why the TEI is a suitable framework for the encoding of CMC corpora. We propose a model of basic CMC units (utterances, posts, and nonverbal activities) and the macro- and micro-level structures of interactions in CMC environments. Based on these models, we introduce CMC-core, a TEI customisation for the encoding of CMC corpora, which defines CMC-specific encoding features on the four levels of elements, model classes, attribute classes, and modules of the TEI infrastructure. The description of our customisation is illustrated by encoding examples from corpora by researchers of the TEI SIG CMC, representing a variety of CMC genres, i.e. chat, wiki talk, twitter, blog, and Second Life interactions. The material described, i.e. schemata, encoding examples, and documentation, is available from the of the TEI CMC SIG Wiki and will accompany a feature request to the TEI council in late 2019.
CMDI Explorer
(2021)
We present CMDI Explorer, a tool that empowers users to easily explore the contents of complex CMDI records and to process selected parts of them with little effort. The tool allows users, for instance, to analyse virtual collections represented by CMDI records, and to send collection items to other CLARIN services such as the Switchboard for subsequent processing. CMDI Explorer hence adds functionality that many users felt was lacking from the CLARIN tool space.
German research on collocation(s) focuses on many different aspects. A comprehensive documentation would be impossible in this short report. Accepting that we cannot do justice to all the contributions to this area, we just pick out some influential comerstones. This selection does not claim to be representative or balanced, but it follows the idea to constitute the backbone of the story we want to tell: Our ‘German’ view of the still ongoing evolution of a notion of ‘collocation’ Although our own work concerns the theoretical background of and the empirical rationale for collocations, lexicography occupies a large space. Some of the recent publications ( Wahrig 2008, Häcki Buhofer et al. 2014) represent a turn to the empirical legitimation for the selection of typical expressions. Nevertheless, linking the empirical evidence to the needs of an abstract lexicographic description (or a didactic format) is still an open issue.
The paper reports on the results of a scientific colloquium dedicated to the creation of standards and best practices which are needed to facilitate the integration of language resources for CMC stemming from different origins and the linguistic analysis of CMC phenomena in different languages and genres. The key issue to be solved is that of interoperability – with respect to the structural representation of CMC genres, linguistic annotations metadata, and anonymization/pseudonymization schemas. The objective of the paper is to convince more projects to partake in a discussion about standards for CMC corpora and for the creation of a CMC corpus infrastructure across languages and genres. In view of the broad range of corpus projects which are currently underway all over Europe, there is a great window of opportunity for the creation of standards in a bottom-up approach.
We present an approach to making existing CLARIN web services usable for spoken language transcriptions. Our approach is based on a new TEI-based ISO standard for such transcriptions. We show how existing tool formats can be transformed to this standard, how an encoder/decoder pair for the TCF format enables users to feed this type of data through a WebLicht tool chain, and why and how web services operating directly on the standard format would be useful.
Telephone-based remote interpreting has come into widespread use in multilingual encounters, all the more so in times of refugee crises and the large influx of asylum-seekers into Europe. Nevertheless, the linguistic practices in this mode of communication have not yet been examined comprehensively. This article therefore investigates selected aspects of turn-taking and clarification sequences during semi-authentic telephone-interpreted counselling sessions for refugees (Arabic–German). A quantitative analysis reveals that limited audibility makes it more difficult for interpreters to claim their turn successfully; in most cases, however, turn-taking occurs smoothly. The trouble sources that trigger queries are mainly content-related and interpreters vary greatly in the ways they deal with such difficulties. Contrary to what one might expect, the study shows that coordination fails only rarely during telephone-based remote interpreting.
In my talk, I present an empirical approach to detecting and describing proverbs as frozen sentences with specific functions in current language use. We have developed this approach in the EU project ‘SprichWort’ (based on the German Reference Corpus). The first chapter illustrates selected aspects of our complex, iterative procedure to validate proverb candidates. Based on our corpus-driven lexpan methodology of slot analysis I then discuss semantic restrictions of proverb patterns. Furthermore, I show different degrees of proverb quality ranging from genuine proverbs to non-proverb realizations of the same abstract pattern. On the one hand, the corpus validation reveals that proverbs are definitely perceived and used as relatively fixed entities and often as sentences. On the other hand, proverbs are not only interpreted as an interesting unique phenomenon but also as part of the whole lexicon, embedded in networks of different lexical items.
The present paper describes Corpus Query Lingua Franca (ISO CQLF), a specification designed at ISO Technical Committee 37 Subcommittee 4 “Language resource management” for the purpose of facilitating the comparison of properties of corpus query languages. We overview the motivation for this endeavour and present its aims and its general architecture. CQLF is intended as a multi-part specification; here, we concentrate on the basic metamodel that provides a frame that the other parts fit in.
The present paper outlines the projected second part of the Corpus Query Lingua Franca (CQLF) family of standards: CQLF Ontology, which is currently in the process of standardization at the International Standards Organization (ISO), in its Technical Committee 37, Subcommittee 4 (TC37SC4) and its national mirrors. The first part of the family, ISO 24623-1 (henceforth CQLF Metamodel), was successfully adopted as an international standard at the beginning of 2018. The present paper reflects the state of the CQLF Ontology at the moment of submission for the Committee Draft ballot. We provide a brief overview of the CQLF Metamodel, present the assumptions and aims of the CQLF Ontology, its basic structure, and its potential extended applications. The full ontology is expected to emerge from a community process, starting from an initial version created by the authors of the present paper.
Corpus REDEWIEDERGABE
(2020)
This article presents the corpus REDEWIEDERGABE, a German-language historical corpus with detailed annotations for speech, thought and writing representation (ST&WR). With approximately 490,000 tokens, it is the largest resource of its kind. It can be used to answer literary and linguistic research questions and serve as training material for machine learning. This paper describes the composition of the corpus and the annotation structure, discusses some methodological decisions and gives basic statistics about the forms of ST&WR found in this corpus.
In a previous study, Aceves and Evans present a large-scale quantitative information-theoretic analysis of parallel corpus data in ~1,000 languages to show that there are apparently strong associations between the way languages encode information into words and patterns of communication, e.g. the configuration of semantic information. During the peer review process, one reviewer raised the question of the extent to which the presented results depend on different corpus sizes (see the Peer Review File). This is a very important question given that most, if not all, of the quantities associated with word frequency distributions vary systematically with corpus size. While Aceves and Evans claim that corpus size does not affect the results presented, I challenge this view by presenting reanalyses of the data that clearly suggest that it does.
We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
Except for some recent advances in spoken language lexicography (cf. Verdonik & Sepesy Maučec 2017, Hansen & Hansen 2012, Siepmann 2015), traditional lexicographic work is mainly oriented towards the written language. In this paper, we describe a method we used to identify relevant headword candidates for a lexicographic resource for spoken language that is currently being developed at the Institute for the German Language (IDS, Mannheim). We describe the challenges of the headword selection for a dictionary of spoken language, and having made considerations regarding our headword concept, we present the corpus-based procedures that we used in order to facilitate the headword selection. After presenting the results regarding the selection of one-word lemmas, we discuss the opportunities and limitations of our approach.
Speech islands are historically and developmentally unique and will inevitably disappear within the next decades. We urgently need to preserve their remains and exploit what is left in order to make research on language-in-contact and historical as well as current comparative language research possible.
The Archive for Spoken German (AGD) at the Institute for German Language collects, fosters and archives data from completed research projects and makes them available to the wider research community.
Besides large variation corpora and corpora of conversational speech, the archive already contains a range of collections of data on German speech minorities. The latter will be outlined in this chapter. Some speech island data is already made available through the personal service of the AGD, or the database of spoken German (DGD), e.g. data on Australian German, Unserdeutsch, or German in North America. Some corpora are still being prepared for publication, but still important to document for potentially interested research projects. We therefore also explain the current problems and efforts related to the curation of speech island data, from the digitization of recordings and the collection of metadata, to the integration of transcriptions, annotations and other ways of accessing and sharing data.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
We present a method to identify and document a phenomenon on which there is very little empirical data: German phrasal compounds occurring in the form of as a single token (without punctuation between their components). Relying on linguistic criteria, our approach implies to have an operational notion of compounds which can be systematically applied as well as (web) corpora which are large and diverse enough to contain rarely seen phenomena. The method is based on word segmentation and morphological analysis, it takes advantage of a data-driven learning process. Our results show that coarse-grained identification of phrasal compounds is best performed with empirical data, whereas fine-grained detection could be improved with a combination of rule-based and frequency-based word lists. Along with the characteristics of web texts, the orthographic realizations seem to be linked to the degree of expressivity.
In this paper, we present our work-inprogress to automatically identify free indirect representation (FI), a type of thought representation used in literary texts. With a deep learning approach using contextual string embeddings, we achieve f1 scores between 0.45 and 0.5 (sentence-based evaluation for the FI category) on two very different German corpora, a clear improvement on earlier attempts for this task. We show how consistently marked direct speech can help in this task. In our evaluation, we also consider human inter-annotator scores and thus address measures of certainty for this difficult phenomenon.
We start by trying to answer a question that has already been asked by de Schryver et al. (2006): Do dictionary users (frequently) look up words that are frequent in a corpus. Contrary to their results, our results that are based on the analysis of log files from two different online dictionaries indicate that users indeed look up frequent words frequently. When combining frequency information from the Mannheim German Reference Corpus and information about the number of visits in the Digital Dictionary of the German Language as well as the German language edition of Wiktionary, a clear connection between corpus and look-up frequencies can be observed. In a follow-up study, we show that another important factor for the look-up frequency of a word is its temporal social relevance. To make this effect visible, we propose a de-trending method where we control both frequency effects and overall look-up trends.
Dieses Kapitel lotet Möglichkeiten und Methoden aus, digitale Diskursanalysen nationalsozialistischer Quellentexte durchzuführen. Digitale Technologie wird dabei als heuristisches Werkzeug betrachtet, mit dem der Sprachgebrauch während des Nationalsozialismus im Rahmen größerer Quellenkorpora untersucht werden kann. In einem theoretischen Abschnitt wird grundsätzlich dafür plädiert, während des Analyseprozesses hermeneutisches Sinnverstehen mit breitflächigen korpusbasierten Abfragen zu kombinieren. Verdeutlicht wird diese Herangehensweise an zwei empirischen Beispielen: Anhand eines Korpus von Hitler- und Goebbels-Reden wird dem Auftauchen und der diskursiven Ausgestaltung des nationalsozialistischen Konzepts „Lebensraum“ nachgespürt. Schritt für Schritt wird offengelegt, welche Analysewege durch das Abfragen von Schlüsseltexten, Keywords, Konkordanzen und Kollokationen verfolgt werden können. Das zweite Beispiel zeigt anhand von Eingaben, die aus der Bevölkerung an Staats- und Parteiinstanzen gerichtet wurden, wie solche Quellen mithilfe eines digitalen Tools manuell annotiert werden können, um sie danach auf Musterhaftigkeiten im Sprachgebrauch hin auswerten zu können.
This paper investigates emergent pseudo-coordination in spoken German. In a corpus-based study, seven verbs in the first conjunct are analyzed regarding the degree of semantic bleaching and the development of subjective or aspectual meaning components. Moreover, it is shown that each verb shows distinct tendencies for co-ocurrences, especially with deictic adverbs in the first conjunct and with specific verbs and verb classes in the second conjunct. It is argued that pseudo-coordination is originally motivated by the need for ‘chunking’ in unplanned speech and that it is still prominently used in this function in German, in contrast to languages in which pseudo-coordination is grammaticalized further.
We evaluate a graph-based dependency parser on DeReKo, a large corpus of contemporary German. The dependency parser is trained on the German dataset from the SPMRL 2014 Shared Task which contains text from the news domain, whereas DeReKo also covers other domains including fiction, science, and technology. To avoid the need for costly manual annotation of the corpus, we use the parser’s probability estimates for unlabeled and labeled attachment as main evaluation criterion. We show that these probability estimates are highly correlated with the actual attachment scores on a manually annotated test set. On this basis, we compare estimated parsing scores for the individual domains in DeReKo, and show that the scores decrease with increasing distance of a domain to the training corpus.
This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are the depositors’ questionnaire and automatic quality assurance, both developed as web applications. They are accompanied by a Knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we split linguistic data into three resource classes (data deposits, collections and corpora). The class of a resource defines the strictness of the quality assurance it should undergo. This division is introduced so that too strict quality criteria do not prevent researchers from depositing their data.
This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST also develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are a questionnaire and automatic quality assurance for depositors of language resources, both developed as web applications. They are accompanied by a knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we consider three main data maturity levels in order to decide on a suitable level of strictness of the quality assurance. This division has been introduced to avoid that a set of ideal quality criteria prevent researchers from depositing or even assessing their (legacy) data. The tools described in the paper are work in progress and are expected to be released by the end of the QUEST project in 2022.
The paper describes preliminary studies regarding the usage of Example-Based Querying for specialist corpora. We outline an infrastructure for its application within the linguistic domain. Example-Based Querying deals with retrieval situations where users would like to explore large collections of specialist texts semantically, but are unable to explicitly name the linguistic phenomenon they look for. As a way out, the proposed framework allows them to input prototypical everyday language examples or cases of doubt, which are automatically processed by CRF and linked to appropriate linguistic texts in the corpus.
Language resources are often compiled for the purpose of variational analysis, such as studying differences between genres, registers, and disciplines, regional and diachronic variation, influence of gender, cultural context, etc. Often the sheer number of potentially interesting contrastive pairs can get overwhelming due to the combinatorial explosion of possible combinations. In this paper, we present an approach that combines well understood techniques for visualization heatmaps and word clouds with intuitive paradigms for exploration drill down and side by side comparison to facilitate the analysis of language variation in such highly combinatorial situations. Heatmaps assist in analyzing the overall pattern of variation in a corpus, and word clouds allow for inspecting variation at the level of words.
The landscape of digital lexical resources is often characterized by dedicated local portals and proprietary interfaces as primary access points for scholars and the interested public. In addition, legal and technical restrictions are potential issues that can make it difficult to efficiently query and use these valuable resources. As part of the research data consortium Text+, solutions for the storage and provision of digital language resources are being developed and provided in the context of the unified cross-domain German research data infrastructure NFDI. The specific topic of accessing lexical resources in a diverse and heterogenous landscape with a variety of participating institutions and established technical solutions is met with the development of the federated search and query framework LexFCS. The LexFCS extends the established CLARIN Federated Content Search that already allows accessing spatially distributed text corpora using a common specification of technical interfaces, data formats, and query languages. This paper describes the current state of development of the LexFCS, gives an insight into its technical details, and provides an outlook on its future development.
We present a fine-grained NER annotations scheme with 30 labels and apply it to German data. Building on the OntoNotes 5.0 NER inventory, our scheme is adapted for a corpus of transcripts of biographic interviews by adding categories for AGE and LAN(guage) and also adding label classes for various numeric and temporal expressions. Applying the scheme to the spoken data as well as a collection of teaser tweets from newspaper sites, we can confirm its generality for both domains, also achieving good inter-annotator agreement. We also show empirically how our inventory relates to the well-established 4-category NER inventory by re-annotating a subset of the GermEval 2014 NER coarse-grained dataset with our fine label inventory. Finally, we use a BERT-based system to establish some baselines for NER tagging on our two new datasets. Global results in in-domain testing are quite high on the two datasets, near what was achieved for the coarse inventory on the CoNLLL2003 data. Cross-domain testing produces much lower results due to the severe domain differences.
We present a collection of (currently) about 5.500 commands directed to voice-controlled virtual assistants (VAs) by sixteen initial users of a VA system in their homes. The collection comprises recordings captured by the VA itself and with a conditional voice recorder (CVR) selectively capturing recordings including the VA-directed commands plus some surrounding context. Next to a description of the collection, we present initial findings on the patterns of use of the VA systems during the first weeks after installation, including usage timing, the development of usage frequency, distributions of sentence structures across commands, and (the development of) command success rates. We discuss the advantages and disadvantages of the applied collection-specific recording approach and describe potential research questions that can be investigated in the future, based on the collection, as well as the merit of combining quantitative corpus linguistic approaches with qualitative in-depth analyses of single cases.
In this paper, we present a GOLD standard of part-of-speech tagged transcripts of spoken German. The GOLD standard data consists of four annotation layers – transcription (modified orthography), normalization (standard orthography), lemmatization and POS tags – all of which have undergone careful manual quality control. It comes with guidelines for the manual POS annotation of transcripts of German spoken data and an extended version of the STTS (Stuttgart Tübingen Tagset) which accounts for phenomena typically found in spontaneous spoken German. The GOLD standard was developed on the basis of the Research and Teaching Corpus of Spoken German, FOLK, and is, to our knowledge, the first such dataset based on a wide variety of spontaneous and authentic interaction types. It can be used as a basis for further development of language technology and corpus linguistic applications for German spoken language.
In many countries of the world, perspectives on gender equality and racism have changed in recent decades. One result has been more attention being devoted to traces of androcentric and racist language in society. This also affects dictionaries. In lexicography there are discussions about whether or to what extent social asymmetries are inscribed in dictionaries and if this is still acceptable. The issue of the nature of description plays an important role in this discussion. If sexist usages are often found in language use, i.e. in the corpus data on which the dictionary is based, does the dictionary also have to show them? How is this, in turn, compatible with the normative power of dictionaries? Do dictionaries contribute to the perpetuation of gender stereotypes by showcasing them under the banner of descriptive principles? And what roles do lexicographers play in this process? The article deals with these questions on the basis of individual lexicographical examples and current discussions in the lexicographic and public community.
Annotated dataset consisting of personal designations found on websites of 42 German, Austrian, Swiss and South Tyrolean cities. Our goal is to re-evaluate the websites every year in order to see how the use of gender-fair language develops over time. The dataset contains coordinates for the creation of map material.
We present a novel NLP resource for the explanation of linguistic phenomena, built and evaluated exploring very large annotated language corpora. For the compilation, we use the German Reference Corpus (DeReKo) with more than 5 billion word forms, which is the largest linguistic resource worldwide for the study of contemporary written German. The result is a comprehensive database of German genitive formations, enriched with a broad range of intra- und extralinguistic metadata. It can be used for the notoriously controversial classification and prediction of genitive endings (short endings, long endings, zero-marker). We also evaluate the main factors influencing the use of specific endings. To get a general idea about a factor’s influences and its side effects, we calculate chi-square-tests and visualize the residuals with an association plot. The results are evaluated against a gold standard by implementing tree-based machine learning algorithms. For the statistical analysis, we applied the supervised LMT Logistic Model Trees algorithm, using the WEKA software. We intend to use this gold standard to evaluate GenitivDB, as well as to explore methodologies for a predictive genitive model.
This article sketches the development of paronym dictionaries in German. These dictionaries document and describe commonly confused words which cause uncertainties because they are similar in sound, spelling and/or meaning (e.g. effektiv/effizient, sportlich/sportiv). First, an overview of existing reference guides is provided, covering different traditions. Numerous lemma lists have been collected for pedagogical purposes and there has always been an interest in the lexicological treatment of paronyms. However, only a handful of dictionaries covering commonly confused pairs and a small number of genuine paronym dictionaries have ever been compiled. I will focus on lexicographic endeavours, including Wustmann (1891), Müller (1973) and Pollmann and Wolk (2001). Secondly, I will shed light on the differences in descriptions in these dictionaries. This includes how prescriptive approaches have been replaced over time by empirical descriptive accounts and how dictionaries have moved away from restricted, static hardback editions towards dynamic e-dictionaries. Finally, an e-dictionary, “Paronyme — Dynamisch im Kontrast”, is presented with contrastive and flexible two-level consultation views. Its three key elements are its corpus-based foundation, the implementation of meta-lexicographic requirements and a consideration of users’ interests. This dictionary has implemented a user-friendly and dynamic interface and it records conventionalized patterns and preferences in authentic communication.
Grammar and corpora 2016
(2018)
In recent years, the availability of large annotated and searchable corpora, together with a new interest in the empirical foundation and validation of linguistic theory and description, has sparked a surge of novel and interesting work using corpus-based methods to study the grammar of natural languages. However, a look at relevant current research on the grammar of the Germanic, Romance, and Slavic languages reveals a variety of different theoretical approaches and empirical foci, which can be traced back to different philological and linguistic traditions. Still, this current state of affairs should not be seen as an obstacle but as an ideal basis for a fruitful exchange of ideas between different research paradigms.
In recent years, the availability of large annotated and searchable corpora, together with a new interest in the empirical foundation and validation of linguistic theory and description, has sparked a surge of novel and interesting work using corpus-based methods to study the grammar of natural languages. However, a look at relevant current research on the grammar of the Germanic, Romance, and Slavic languages reveals a variety of different theoretical approaches and empirical foci, which can be traced back to different philological and linguistic traditions. Still, this current state of affairs should not be seen as an obstacle but as an ideal basis for a fruitful exchange of ideas between different research paradigms.
The possibilities of re-use and archiving of spoken and written corpora are affected by personality rights (depending on legal tradition also called: the right of publicity), copyright law and data protection / privacy laws. These recommendations include information about legal aspects which should be considered while creating corpora to ensure the greatest archivability and re-usability possible in compliance with current laws.
The information compiled here shall serve researchers who plan to create corpora or who are involved in evaluation of such measures as a guideline. This information is not exhaustive or to be considered as legal advice. Researchers should consult institutional legal departments and management before making legally relevant decisions. That said, further legal expertise should be sought if possible as early as project planning phases.
The present paper examines a variety of ways in which the Corpus of Contemporary Romanian Language (CoRoLa) can be used. A multitude of examples intends to highlight a wide range of interrogation possibilities that CoRoLa opens for different types of users. The querying of CoRoLa displayed here is supported by the KorAP frontend, through the querying language Poliqarp. Interrogations address annotation layers, such as the lexical, morphological and, in the near future, the syntactical layer, as well as the metadata. Other issues discussed are how to build a virtual corpus, how to deal with errors, how to find expressions and how to identify expressions.
This paper presents experiments on sentence boundary detection in transcripts of spoken dialogues. Segmenting spoken language into sentence-like units is a challenging task, due to disfluencies, ungrammatical or fragmented structures and the lack of punctuation. In addition, one of the main bottlenecks for many NLP applications for spoken language is the small size of the training data, as the transcription and annotation of spoken language is by far more time-consuming and labour-intensive than processing written language. We therefore investigate the benefits of data expansion and transfer learning and test different ML architectures for this task. Our results show that data expansion is not straightforward and even data from the same domain does not always improve results. They also highlight the importance of modelling, i.e. of finding the best architecture and data representation for the task at hand. For the detection of boundaries in spoken language transcripts, we achieve a substantial improvement when framing the boundary detection problem as a sentence pair classification task, as compared to a sequence tagging approach.
The present thesis introduces KoralQuery, a protocol for the generic representation of queries to linguistic corpora. KoralQuery defines a set of types and operations which serve as abstract representations of linguistic entities and configurations. By combining these types and operations in a nested structure, the protocol may express linguistic structures of arbitrary complexity. It achieves a high degree of neutrality with regard to linguistic theory, as it provides flexible structures that allow for the setting of certain parameters to access several complementing and concurrent sources and layers of annotation on the same textual data. JSON-LD is used as a serialisation format for KoralQuery, which allows for the well-defined and normalised exchange of linguistic queries between query engines to promote their interoperability. The automatic translation of queries issued in any of three supported query languages to such KoralQuery serialisations is the second main contribution of this thesis. By employing the introduced translation module, query engines may also work independently of particular query languages, as their backend technology may rely entirely on the abstract KoralQuery representations of the queries. Thus, query engines may provide support for several query languages at once without any additional overhead. The original idea of a general format for the representation of linguistic queries comes from an initiative called Corpus Query Lingua Franca (CQLF), whose theoretic backbone and practical considerations are outlined in the first part of this thesis. This part also includes a brief survey of three typologically different corpus query languages, thus demonstrating their wide variety of features and defining the minimal target space of linguistic types and operations to be covered by KoralQuery.
This paper discusses the technological and methodological challenges in creating and sharing HAMATAC, the Hamburg Map Task Corpus. The first version of the corpus, consisting of 24 recordings with orthographic transcriptions and metadata, is publicly available. A second version featuring different types of linguistic annotation is in progress. I will describe how the various software tools and data formats of the EXMARaLDA system were used for transcription and multi-level annotation, to compile recordings and transcriptions into a corpus and manage metadata, to publish the corpus, and how they can be used for carrying out corpus queries (KWIC) and analyses. Some recurrent issues in corpus building and sharing and the interaction of technological and methodological aspects will be illustrated using HAMATAC.
Natural language Processing tools are mostly developed for and optimized on newspaper texts, and often Show a substantial performance drop when applied to other types of texts such as Twitter feeds, Chat data or Internet forum posts. We explore a range of easy-to-implement methods of adapting existing part-of-speech taggers to improve their performance on Internet texts. Our results show that these methods can improve tagger performance substantially.
Interoperability in an Infrastructure Enabling Multidisciplinary Research: The case of CLARIN
(2020)
CLARIN is a European Research Infrastructure providing access to language resources and technologies for researchers in the humanities and social sciences. It supports the use and study of language data in general and aims to increase the potential for comparative research of cultural and societal phenomena across the boundaries of languages and disciplines, all in line with the European agenda for Open Science. Data infrastructures such as CLARIN have recently embarked on the emerging frameworks for the federation of infrastructural services, such as the European Open Science Cloud and the integration of services resulting from multidisciplinary collaboration in federated services for the wider domain of the social sciences and humanities (SSH). In this paper we describe the interoperability requirements that arise through the existing ambitions and the emerging frameworks. The interoperability theme will be addressed at several levels, including organisation and ecosystem, design of workflow services, data curation, performance measurement and collaboration. For each level, some concrete outcomes are described.
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divided into 16 parts based on 16 corpus folds. We describe how the dataset was created and structured. By evaluating the distribution over the 16 folds, we show that it is possible to work with a subset of the folds in many use cases (e.g., to save computational resources). In a case study, we investigate the growth of vocabulary (as well as the number of hapax legomena) as an increasing number of folds are included in the analysis. We cross-combine this with the various cleaning stages of the dataset. We also give some guidance in the form of Python, R, and Stata markdown scripts on how to work with the resource.
Over the past decade, conducting empirical research in linguistics has become increasingly popular. The first of its kind, this book provides an engaging and practical introduction to this exciting versatile field, providing a comprehensive overview of research aspects in general, and covering a broad range of subdiscipline-specific methodological approaches. Subfields covered include language documentation and descriptive linguistics, language typology, corpus linguistics, sociolinguistics and anthropological linguistics, cognitive linguistics and psycholinguistics, and neurolinguistics. The book reflects on the strengths and weaknesses of each single approach and on how they interact with one-another across the study of language in its many diverse facets. It also includes exercises, example student projects and recommendations for further reading, along with additional online teaching materials. Providing hands-on experience, and written in an engaging and accessible style, this unique and comprehensive guide will give students the inspiration they need to develop their own research projects in empirical linguistics.
In this article, we provide an insight into the development and application of a corpus-lexicographic tool for finding neologisms that are not yet listed in German dictionaries. As a starting point, we used the words listed in a glossary of German neologisms surrounding the COVID-19 pandemic. These words are lemma candidates for a new dictionary on COVID-19 discourse in German. They also provided the database used to develop and test the NeoRate tool. We report on the lexicographic work in our dictionary project, the design and functionalities of NeoRate, and describe the first test results with the tool, in particular with regard to previously unregistered words. Finally, we discuss further development of the tool and its possible applications.
This presentation introduces a new collaborative project: the International Comparable Corpus (ICC) (https://korpus.cz/icc), to be compiled from European national, standard(ised) languages, using the protocols for text categories and their quantities of texts in the International Corpus of English (ICE).
Introduction
(2019)
The task-oriented and format-driven development of corpus query systems has led to the creation of numerous corpus query languages (QLs) that vary strongly in expressiveness and syntax. This is a severe impediment for the interoperability of corpus analysis systems, which lack a common protocol. In this paper, we present KoralQuery, a JSON-LD based general corpus query protocol, aiming to be independent of particular QLs, tasks and corpus formats. In addition to describing the system of types and operations that Koral- Query is built on, we exemplify the representation of corpus queries in the serialized format and illustrate use cases in the KorAP project.
The General Data Protection Regulation (hereinafter: GDPR), EU Regulation 2016/679 of 27 April 2016, will become applicable on 25 May 2018 and repeal the Personal Data Directive of 24 October 1995.
Unlike a directive, which requires transposition into national laws (while leaving the choice of “forms and methods” to the Member States), a regulation is binding and directly applicable in all Member States. This means that when the GDPR becomes applicable, all the EU countries will have the same rules regarding the protection of personal data — at least in principle, since some details (including in the area of research — see below) are expressly left to the discretion of the Member States.
The GDPR is a particularly ambitious piece of legislation (consisting of 99 articles and 173 recitals) whose intended territorial scope extends beyond the borders of the European Union. Its main concepts and principles are essentially similar to those of the Personal Data Directive, but enriched with interpretation developed through the case law of the CJEU and the opinions of the Article 29 Data Protection Working Party (hereinafter: WP29).
This White Paper will discuss the main principles of data protection and their impact on language resources, as well as special rules regarding research under the GDPR and the standardisation mechanisms recognized by the Regulation.
Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs—ranging from very simple n-gram models to state-of-the-art deep neural networks—on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.
CoMParS is a resource under construction in the context of the long-term project German Grammar in European Comparison (GDE) at the IDS Mannheim. The principal goal of GDE is to create a novel contrastive grammar of German against the background of other European languages. Alongside German, which is the central focus, the core languages for comparison are English, French, Hungarian and Polish, representing different typological classes. Unlike traditional contrastive grammars available for German, which usually cover language pairs and are based on formal grammatical categories, the new GDE grammar is developed in the spirit of functionalist typology. This implies that, instead of formal criteria, cognitively motivated functional domains in terms of Givón (1984) are used as tertia comparationis. The purpose of CoMParS is to document the empirical basis of the theoretical assumptions of GDE-V and to illustrate the otherwise rather abstract content of grammar books by as many as possible naturally occurring and adequately presented multilingual examples, including information on their use in specific contexts and registers. These examples come from existing parallel corpora, and our presentation will focus on the legal aspects and consequences of this choice of language data.
This paper gives an insight into the basic concepts for a corpus-based lexical resource of spoken German, which is being developed by the project "The Lexicon of Spoken German"(Lexik des gesprochenen Deutsch, LeGeDe) at the "Institute for the German Language" (Institut für Deutsche Sprache, IDS) in Mannheim. The focus of the paper is on initial ideas of semi-automatic and automatic resources that assist the quantitative analysis of the corpus data for the creation of dictionary content. The work is based on the "Research and Teaching Corpus of Spoken German" (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK).
Less than one percent of words would be affected by gender-inclusive language in German press texts
(2024)
Research on gender and language is tightly knitted to social debates on gender equality and non-discriminatory language use. Psycholinguistic scholars have made significant contributions in this field. However, corpus-based studies that investigate these matters within the context of language use are still rare. In our study, we address the question of how much textual material would actually have to be changed if non-gender-inclusive texts were rewritten to be gender-inclusive. This quantitative measure is an important empirical insight, as a recurring argument against the use of gender-inclusive German is that it supposedly makes written texts too long and complicated. It is also argued that gender-inclusive language has negative effects on language learners. However, such effects are only likely if gender-inclusive texts are very different from those that are not gender-inclusive. In our corpus-linguistic study, we manually annotated German press texts to identify the parts that would have to be changed. Our results show that, on average, less than 1% of all tokens would be affected by gender-inclusive language. This small proportion calls into question whether gender-inclusive German presents a substantial barrier to understanding and learning the language, particularly when we take into account the potential complexities of interpreting masculine generics.
In this paper, we present our experiences and decisions in dealing with challenges in developing, maintaining and operating online research software tools in the field of linguistics. In particular, we highlight reproducibility, dependability, and security as important aspects of quality management – taking into account the special circumstances in which research software
is usually created.
While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models. In this paper, we propose a shift of focus from change detection to change discovery, i.e., discovering novel word senses over time from the full corpus vocabulary. By heavily fine-tuning a type-based and a token-based approach on recently published German data, we demonstrate that both models can successfully be applied to discover new words undergoing meaning change. Furthermore, we provide an almost fully automated framework for both evaluation and discovery.
Providing online repositories for language resources is one of the main activities of CLARIN centres. The legal framework regarding liability of Service Providers for content uploaded by their users has recently been modified by the new Directive on Copyright in the Digital Single Market. A new category of Service Providers, Online Content-Sharing Service Providers (OCSSPs), was added. It is subject to a complex and strict framework, including the requirement to obtain licenses from rightholders for the hosted content. This paper provides the background and effect of these changes to law and aims to initiate a debate on how CLARIN repositories should navigate this new legal landscape.