Open Access

Die Untersuchung von Positionierungsaktivitäten zur diskursiven Herstellung sozialer Identität blickt auf eine lange Tradition zurück und wird innerhalb der Sprachwissenschaft hauptsächlich in der gesprächsanalytischen Erzählforschung angewendet. Im Rahmen eines sozialkonstruktivistischen Ansatzes geht die Positionierungstheorie von einer dynamischen Konstitution von Identität aus. Bisher fehlte es noch an einer systematischen Betrachtung von interaktiven Positionierungsaktivitäten, die sich mit der Realisierung und Aushandlung von Positionierungen in Alltagsgesprächen befasst. Hier setzt diese Arbeit an: Im Rahmen eines interaktionslinguistischen Ansatzes werden Positionierungspraktiken systematisch in vorwiegend nicht-narrativen Kontexten betrachtet. Auf der Grundlage empirischer Analysen liefert die Untersuchung neue Einblicke in die interaktive Konstitution von Identität, ihre sequenziellen Regelhaftigkeiten, Erwartungsstrukturen sowie in das Verhältnis von Selbst- und Fremdpositionierung.

Eine gut entwickelte Schreibkompetenz bildet eine wesentliche Schlüsselqualifikation für die gesellschaftliche Teilhabe in literalisierten Gesellschaften. Aus diesem Grund kommt auch der Schreibdidaktik als Teildisziplin der Sprachdidaktik, die sich mit der Konzeption, Diagnostik und Förderung von Schreibkompetenz auseinandersetzt, eine wichtige Bedeutung zu. Ihr Erkenntnisinteresse besteht vorrangig in der Frage, wie die Aneignung von Schreibkompetenz in Abhängigkeit von den individuellen Lernvoraussetzungen durch unterrichtliche Förderung gelingen kann. Die Bibliografie verfolgt das Ziel, einen Überblick über zentrale Themengebiete und Konzepte der Schreibdidaktik, wie z. B. Schreibkompetenz, Schreibentwicklung, Schreibaufgaben und Schreibunterricht, zu geben. Dafür systematisiert sie einschlägige, aktuelle Literatur und führt neben Internetressourcen zentrale (Beiträge in) Zeitschriften, Sammelbände und Handbücher sowie Einführungen auf.

MULLE is a tool for language learning that focuses on teaching Latin as a foreign language. It is aimed for easy integration into the traditional classroom setting and syllabus, which makes it distinct from other language learning tools that provide standalone learning experience. It uses grammar-based lessons and embraces methods of gamification to improve the learner motivation. The main type of exercise provided by our application is to practice translation, but it is also possible to shift the focus to vocabulary or morphology training.

We describe a simple and efficient Java object model and application programming interface (API) for (possibly multi-modal) annotated natural language corpora. Corpora are represented as elements like Sentences, Turns, Utterances, Words, Gestures and Markables. The API allows linguists to access corpora in terms of these discourse-level elements, i.e. at a conceptual level they are familiar with, with the flexibility offered by a general purpose programming language. It is also a contribution to corpus standardization efforts because it is based on a straightforward and easily extensible data model which can serve as a target for conversion of different corpus formats.

We present a language learning application that relies on grammars to model the learning outcome. Based on this concept we can provide a powerful framework for language learning exercises with an intuitive user interface and a high reliability. Currently the application aims to augment existing language classes and support students by improving the learner attitude and the general learning outcome. Extensions beyond that scope are promising and likely to be added in the future.

Current Natural Language Processing (NLP) systems feature high-complexity processing pipelines that require the use of components at different levels of linguistic and application specific processing. These components often have to interface with external e.g. machine learning and information retrieval libraries as well as tools for human annotation and visualization. At the UKP Lab, we are working on the Darmstadt Knowledge Processing Software Repository (DKPro) (Gurevych et al., 2007a; Müller et al., 2008) to create a highly flexible, scalable and easy-to-use toolkit that allows rapid creation of complex NLP pipelines for semantic information processing on demand. The DKPro repository consists of several main parts created to serve the purposes of different NLP application areas

In this paper we investigate the problem of grammar inference from a different perspective. The common approach is to try to infer a grammar directly from example sentences, which either requires a large training set or suffers from bad accuracy. We instead view it as a problem of grammar restriction or sub-grammar extraction. We start from a large-scale resource grammar and a small number of examples, and find a sub-grammar that still covers all the examples. To do this we formulate the problem as a constraint satisfaction problem, and use an existing constraint solver to find the optimal grammar. We have made experiments with English, Finnish, German, Swedish and Spanish, which show that 10–20 examples are often sufficient to learn an interesting domain grammar. Possible applications include computer-assisted language learning, domain-specific dialogue systems, computer games, Q/A-systems, and others.

Controlled Natural Languages (CNLs) have many applications including document authoring, automatic reasoning on texts and reliable machine translation, but their application is not limited to these areas. We explore a new application area of CNLs, the use of CNLs in computer-assisted language learning. In this paper we present a a web application for language learning using CNLs as well as a detailed description of the properties of the family of CNLs it uses.

Inhaltlich unveränderte Neuauflage. Die Arbeit von Pamela Pachl entdeckt ein Feld künstlerischer Formen, die sich längst jenseits der anwendungsbezogenen Graphik als Sammlerobjekte in hochdifferenzierten Subkulturen etabliert haben. Thema dieser Arbeit sind Skatesticker. Skatesticker sind graphisch gestaltete Aufkleber, die im Besonderen in der Subkultur der Skater gesammelt, gehandelt und verehrt werden. Hergestellt werden die Sticker von Skatecompanys. Ursprünglich zu Werbezwecken produziert, wurden die Sticker zu einem autonomen Ausdruckszeichen des Skater-Lifestyles. Aufgrund der Qualität der graphischen und ästhetischen Gestaltung verlangt dieses Phänomen der Neuzeit geradezu nach einer wissenschaftlichen Untersuchung. Pamela Pachl hat hier ein neues, bisher nicht institutionell legitimiertes Feld entdeckt, seine Konturen und verschiedene Aspekte seiner internen Struktur beschrieben. Dieses Buch richtet sich sowohl an Wissenschaftler verschiedenster Fachrichtungen, wie Kunstwissenschaft, Germanistik und Soziologie als auch an Skater und an der Skateboardkultur Interessierte.

We present a light-weight tool for the annotation of linguistic data on multiple levels. It is based on the simplification of annotations to sets of markables having attributes and standing in certain relations to each other. We describe the main features of the tool, emphasizing its simplicity, customizability and versatility

In this paper we show that the extraction of opinions from free-text reviews can improve the accuracy of movie recommendations. We present three approaches to extract movie aspects as opinion targets and use them as features for the collaborative filtering. Each of these approaches requires different amounts of manual interaction. We collected a data set of reviews with corresponding ordinal (star) ratings of several thousand movies to evaluate the different features for the collaborative filtering. We employ a state-of-the-art collaborative filtering engine for the recommendations during our evaluation and compare the performance with and without using the features representing user preferences mined from the free-text reviews provided by the users. The opinion mining based features perform significantly better than the baseline, which is based on star ratings and genre information only.

Dictionaries have been part and parcel of literate societies for many centuries. They assist in communication, particularly across different languages, to aid in understanding, creating, and translating texts. Communication problems arise whenever a native speaker of one language comes into contact with a speaker of another language. At the same time, English has established itself as a lingua franca of international communication. This marked tendency gives lexicography of English a particular significance, as English dictionaries are used intensively and extensively by huge numbers of people worldwide.

With OWIDplusLIVE, we would like to introduce the EURALEX community to two resources that provide analytical access to daily updated data (data: frequency data and N-grams – reference point: previous day).

This paper addresses the question of why we face unsatisfactory German dictionary entries when looking up and comparing two similar lexical terms that are loan words, new words, (near)-synonyms, or confusables. It explains how users are aware of existing reference works but still search or post on language forums, often after consulting a dictionary and experiencing a range of dictionary-based problems. Firstly, these dictionary-based difficulties will be scrutinised in more detail with respect to content, function, presentation, and the language of definitions. Entries documenting loan words and commonly confused pairs from different lexical reference resources serve as examples to show the shortcomings. Secondly, I will explain why learning about your target group involves studying discussion forums. Forums are a valuable source for detailed user studies, enabling the examination of different communicative needs, concrete linguistic questions, speakers’ intuitions, and people’s reactions to posts and comments. Thirdly, with the help of two examples I will describe how the study of chats and forums had a major impact on the development of a recently compiled German dictionary of confusables. Finally, that same problem-solving approach is applied to the idea of a future dictionary of neologisms and their synonyms.

Not only professional lexicographers, but also people without a professional background in lexicography, have reacted to the increased need for information on new words or medical and epidemiological terms being used in the context of the COVID-19 pandemic. In this study, corona-related glossaries published on German news websites are presented, as well as different kinds of responses from professional lexicography. They are compared in terms of the amount of encyclopaedic information given and the methods of definition used. In this context, answers to corona-related words from a German questionanswer platform are also presented and analyzed. Overall, these different reactions to a unique challenge shed light on the importance of lexicography for society and vice versa.

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.

Der Beitrag steht im Zusammenhang mit einem Forschungsprojekt, das die Erarbeitung einer sprachlichen Sozialgeschichte der Jahre 1933 bis 1945 zum Ziel hat. Er verfolgt das Ziel, zum einen die Kategorie der Alltagsdissidenz methodisch-theoretisch im Searleschen Sinn von Akzeptanzverweigerung zu konzipieren und empirisch zu erproben. Außerdem wird damit ein bisher diskurslinguistisch nicht beachteter Aspekt der Sozialgeschichte im NS sprachgeschichtlich erschlossen. Materialgestützt werden Formen von Alltagsdissidenz vorgestellt und in ein, nach Beteiligung und Öffentlichkeitsgrad unterscheidendes Ordnungsschema gebracht.

We present a supervised machine learning AND system which tackles semantic similarity between publication titles by means of word embeddings. Word embeddings are integrated as external components, which keeps the model small and efficient, while allowing for easy extensibility and domain adaptation. Initial experiments show that word embeddings can improve the Recall and F score of the binary classification sub-task of AND. Results for the clustering sub-task are less clear, but also promising and overall show the feasibility of the approach.

We demonstrate the utility of word embedding-based semantic similarity methods for Author Name Disambiguation.

We present an implemented machine learning system for the automatic detection of nonreferential it in spoken dialog. The system builds on shallow features extracted from dialog transcripts. Our experiments indicate a level of performance that makes the system usable as a preprocessing filter for a coreference resolution system. We also report results of an annotation study dealing with the classification of it by naive subjects.

This thesis describes work in three areas: grammar engineering, computer-assisted language learning and grammar learning. These three parts are connected by the concept of a grammar-based language learning application. Two types of grammars are of concern. The first we call resource grammars, extensive descriptions a natural languages. Part I focuses on this kind of grammars. The other are domain-specific or application-specific grammars. These grammars only describe a fragment of natural language that is determined by the domain of a certain application. Domain-specific grammars are relevant for Part II and Part III. Another important distinction is between humans learning a new natural language using computational grammars (Part II) and computers learning grammars from example sentences (Part III). Part I of this thesis focuses on grammar engineering and grammar testing. It describes the development and evaluation of a computational resource grammar for Latin. Latin is known for its rich morphology and free word order, both have to be handled in a computationally efficient way. A special focus is on methods how computational grammars can be evaluated using corpus data. Such an evaluation is presented for the Latin resource grammar. Part II, the central part, describes a computer-assisted language learning application based on domain-specific grammars. The language learning application demonstrates how computational grammars can be used to guide the user input and how language learning exercises can be modeled as grammars. This allows us to put computational grammars in the center of the design of language learning exercises used to help humans learn new languages. Part III, the final part, is dedicated to a method to learn domain- or application-specific grammars based on a wide-coverage grammar and small sets of example sentences. Here a computer is learning a grammar for a fragment of a natural language from example sentences, potentially without any additional human intervention. These learned grammars can be based e.g. on the Latin resource grammar described in Part II and used as domain-specific lesson grammars in the language learning application described Part II.

Skatesticker sind grafisch gestaltete Aufkleber, die von Skatelabels – den Herstellern von Skateboards und Zubehör – distribuiert werden. Ursprünglich zu reinen Werbezwecken produziert, haben sich Skatesticker als Symbole der Szene etabliert: Befragte Skater bekennen, dass Skatesticker ein „Ausdruck eines Lebensgefühls“, ein „visueller Eindruck unserer Gefühle“ und eine „[e]infache Möglichkeit[,] sich einer Gruppe zuzuordnen“ sind. Sie werden von Skatern gesammelt, gehandelt und wertgeschätzt. Die vorliegende Arbeit verfolgt einen bildwissenschaftlich orientierten Forschungsansatz, der es ermöglicht, die komplexen – oftmals bildende Kunst adaptierenden – Bildmotive dieser Grafikdesignobjekte und ihre zunehmend autonomisierten Funktionen als visuelle Medien einer Szene zu analysieren und anzuerkennen.

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.

Contents: 1. Vasile Pais, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Roxana Micu and Carol Luca Gasan: Challenges in Creating a Representative Corpus of Romanian Micro-Blogging Text. Pp. 1-7 2. Modest von Korff: Exhaustive Indexing of PubMed Records with Medical Subject Headings. Pp. 8-15 3. Luca Brigada Villa: UDeasy: a Tool for Querying Treebanks in CoNLL-U Format. Pp. 16-19 4. Nils Diewald: Matrix and Double-Array Representations for Efficient Finite State Tokenization. Pp. 20-26 5. Peter Fankhauser and Marc Kupietz: Count-Based and Predictive Language Models for Exploring DeReKo. Pp. 27-31 6. Hanno Biber: “The word expired when that world awoke.” New Challenges for Research with Large Text Corpora and Corpus-Based Discourse Studies in Totalitarian Times. Pp. 32-35

In this paper, we address two problems in indexing and querying spoken language corpora with overlapping speaker contributions. First, we look into how token distance and token precedence can be measured when multiple primary data streams are available and when transcriptions happen to be tokenized, but are not synchronized with the sound at the level of individual tokens. We propose and experiment with a speaker based search mode that enables any speaker’s transcription tier to be the basic tokenization layer whereby the contributions of other speakers are mapped to this given tier. Secondly, we address two distinct methods of how speaker overlaps can be captured in the TEI based ISO Standard for Spoken Language Transcriptions (ISO 24624:2016) and how they can be queried by MTAS – an open source Lucene-based search engine for querying text with multilevel annotations. We illustrate the problems, introduce possible solutions and discuss their benefits and drawbacks.

In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with some interesting exceptions, Wikipedia is superior to WordNet when it comes to the coverage of information necessary to resolve the bridging anaphors in our data set. We further describe a simple procedure for the automatic extraction of the required knowledge from Wikipedia by means of an API, and discuss some of the implications of the procedure’s performance.

We present an implemented system for the resolution of it, this, and that in transcribed multi-party dialog. The system handles NP-anaphoric as well as discourse-deictic anaphors, i.e. pronouns with VP antecedents. Selectional preferences for NP or VP antecedents are determined on the basis of corpus counts. Our results show that the system performs significantly better than a recency-based baseline.

In this paper, we present a suite of flexible UIMA-based components for information retrieval research which have been successfully used (and re-used) in several projects in different application domains. Implementing the whole system as UIMA components is beneficial for configuration management, component reuse, implementation costs, analysis and visualization.

Korpora sind – als idealerweise digital verfüg- und auswertbare Sammlungen von Texten – eine wertvolle empirische Grundlage linguistischer Studien. Eigene Korpora aufzubauen ist, je nach Sprachausschnitt, mit unterschiedlichen Herausforderungen verbunden. Zu allen Texten sollten Metadaten zu den Textentstehungsbedingungen (Zeit, Quelle usw.) erhoben werden, um diese als Variablen in Auswertungen einbeziehen zu können. Andere Informationen wie etwa die Themenzugehörigkeit (oder Annotationen auch unterhalb der Textebene) sind auch hilfreich, in vielerlei Hinsicht aber schwieriger pauschal taxonomisch vorzugeben, geschweige denn, operationell zu ermitteln. Jenseits der »materiellen« Verfügbarkeit der Texte und der technischen Aufbereitung sind es das Urheberrecht, vor allem Lizenz- bzw. Nutzungsrechte, sowie ethische Verantwortung und Persönlichkeitsrechte, die beachtet werden müssen, auch um zu gewährleisten, dass die Daten für die Reproduktion der Studien Dritten rechtssicher zugänglich gemacht werden dürfen. Bevor für ein Vorhaben ein neues Korpus aufgebaut wird, sollte deshalb am besten geprüft werden, ob nicht ein geeignetes bereits zur Verfügung steht. Wenn ein Korpus aufgebaut wird, sollte für eine nachhaltige Aufbewahrung und Zugänglichmachung gesorgt und die Existenz an geeigneter Stelle dokumentiert werden.

Spontan kreierte Okkasionalismen sind rekurrenter Bestandteil verbaler Interaktionen. Vor dem Hintergrund, dass die Bedeutung von Okkasionalismen nicht konventionalisiert und damit potenziell unbekannt ist, untersucht der vorliegende Beitrag aus gesprächsanalytischer Perspektive die Frage, unter welchen Bedingungen die Bedeutung okkasioneller Ausdrücke in Folgeäußerungen selbstinitiiert oder fremdinitiiert erklärt wird und wann dies nicht der Fall ist. Es zeigt sich, dass die überwältigende Mehrheit der 1.068 analysierten Okkasionalismen aus verschiedenen Gründen kein Verstehensproblem darstellt. Wird die Bedeutung eines Okkasionalismus dennoch selbstinitiiert erklärt, dient dies oft anderen Zwecken als der Verstehenssicherung. Wird dagegen die Bedeutung eines nicht problemlos erschließbaren Okkasionalismus nicht unmittelbar selbstinitiiert erläutert, dient der ‚rätselhafte‘ Ausdruck als interaktive Ressource dazu, Rezipient/-innen neugierig zu machen, Nachfragen zu elizitieren und damit Folgeäußerungen zu lizenzieren.

In a recent article, Meylan and Griffiths (Meylan & Griffiths, 2021, henceforth, M&G) focus their attention on the significant methodological challenges that can arise when using large-scale linguistic corpora. To this end, M&G revisit a well-known result of Piantadosi, Tily, and Gibson (2011, henceforth, PT&G) who argue that average information content is a better predictor of word length than word frequency. We applaud M&G who conducted a very important study that should be read by any researcher interested in working with large-scale corpora. The fact that M&G mostly failed to find clear evidence in favor of PT&G's main finding motivated us to test PT&G's idea on a subset of the largest archive of German language texts designed for linguistic research, the German Reference Corpus consisting of ∼43 billion words. We only find very little support for the primary data point reported by PT&G.

We present WOMBAT, a Python tool which supports NLP practitioners in accessing word embeddings from code. WOMBAT addresses common research problems, including unified access, scaling, and robust and reproducible preprocessing. Code that uses WOMBAT for accessing word embeddings is not only cleaner, more readable, and easier to reuse, but also much more efficient than code using standard in-memory methods: a Python script using WOMBAT for evaluating seven large word embedding collections (8.7M embedding vectors in total) on a simple SemEval sentence similarity task involving 250 raw sentence pairs completes in under ten seconds end-to-end on a standard notebook computer.

In this contribution we present some work of the R&D European project “LIRICS” and of the ISO/TC 37/SC 4 committee related to the topic of interoperability and re-use of language resources. We introduce some basic mechanisms of the standardization work in ISO and describe in more details the general approach on how to cope with the annotation of language data within ISO.

Wenn alle Forschungsfragen gestellt, alle Hypothesen formuliert, alle Korpora kompiliert und alle Daten von Proband*innen gesammelt wurden, befinden Sie sich auf einer der letzten Etappen Ihrer linguistischen Studie: der Analyse der Daten. In diesem Kapitel werden Sie einige Werkzeuge kennenlernen, die Sie dabei unterstützen können. Hier nehmen wir an, dass Sie in irgendeiner Form eine quantitative statistische Auswertung vornehmen möchten, denn für qualitative Analysen sind die Werkzeuge, die wir Ihnen vorstellen werden, weniger bis gar nicht geeignet.

We describe a simple procedure for the automatic creation of word-level alignments between printed documents and their respective full-text versions. The procedure is unsupervised, uses standard, off-the-shelf components only, and reaches an F-score of 85.01 in the basic setup and up to 86.63 when using pre- and post-processing. Potential areas of application are manual database curation (incl. document triage) and biomedical expression OCR.

We introduce a novel scientific document processing task for making previously inaccessible information in printed paper documents available to automatic processing. We describe our data set of scanned documents and data records from the biological database SABIO-RK, provide a definition of the task, and report findings from preliminary experiments. Rigorous evaluation proved challenging due to lack of gold-standard data and a difficult notion of correctness. Qualitative inspection of results, however, showed the feasibility and usefulness of the task.