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A "polyglottal" speech synthesis - modifications for a replica of Kempelen's speaking machine
(2019)
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.
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.
We present a descriptive analysis on the two datasets from the shared task on Source, Subjective Expression and Target Extraction from Political Speeches (STEPS), the only existing German dataset for opinion role extraction of its size. Our analysis discusses the individual properties of the three components, subjective expressions, sources and targets and their relations towards each other. Our observations should help practitioners and researchers when building a system to extract opinion roles from German data.
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.
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.
A Supervised learning approach for the extraction of opinion sources and targets from German text
(2019)
We present the first systematic supervised learning approach for the extraction of opinion sources and targets on German language data. A wide choice of different features is presented, particularly syntactic features and generalization features. We point out specific differences between opinion sources and targets. Moreover, we explain why implicit sources can be extracted even with fairly generic features. In order to ensure comparability our classifier is trained and tested on the dataset of the STEPS shared task.
The Lehnwortportal Deutsch (2012 seqq.) serves as an integrated online information system on German lexical borrowings into other languages, synthesizing an increasing number of lexicographical dictionaries and providing basic cross-resource search options. The paper discusses the far-reaching revision of the system’s conceptual, lexicographical and technological underpinnings currently under way, focussing on their relevance for multilingual loanword lexicography.
In this paper we present an experimental semantic search function, based on word embeddings, for an integrated online information system on German lexical borrowings into other languages, the Lehnwortportal Deutsch (LWPD). The LWPD synthesizes an increasing number of lexicographical resources and provides basic cross-resource search options. Onomasiological access to the lexical units of the portal is a highly desirable feature for many research questions, such as the likelihood of borrowing lexical units with a given meaning (Haspelmath & Tadmor, 2009; Zeller, 2015). The search technology is based on multilingual pre-trained word embeddings, and individual word senses in the portal are associated with word vectors. Users may select one or more among a very large number of search terms, and the database returns lexical items with word sense vectors similar to these terms. We give a preliminary assessment of the feasibility, usability and efficacy of our approach, in particular in comparison to search options based on semantic domains or fields.
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.
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).
Besides English, Afrikaans is considered “the [Germanic] language which deviates grammatically the farthest from the others” (Harbert 2007: 17). But how exactly do we measure “grammatical deviation”, and how deviant is Afrikaans really if we compare it not just to other standard languages but also to non-standard varieties? The present contribution aims to address those questions combining functional-typological and dialectometric perspectives. We first select data for 28 Germanic varieties showing vastly different speaker numbers, grades of standardisation and amounts of language contact. Based on 48 (micro)typological variables from syntax, morphology and phonology, we perform cluster analysis and multidimensional scaling and present ways of visualizing and interpreting the results. Inter alia, the analyses show a major divide between Continental West Germanic and North Germanic (as might be expected) and they also identify a number of outliers, including English and pidgin and creole languages such as Russenorsk or Rabaul Creole German. Afrikaans appears to cluster with the other West Germanic languages rather than the outliers. Within West Germanic, however, it does indeed emerge as rather deviant and, according to our metric, it is, for example, typologically closer to other high-contact varieties such as Yiddish than it is to Dutch.
This paper presents a dictionary writing system developed at the Institute for the German Language in Mannheim (IDS) for an ongoing international lexicographical project that traces the way of German loanwords in the East Slavic languages Russian, Belarusian and Ukrainian that were possibly borrowed via Polish. The results will be published in the Lehnwortportal Deutsch (LWP, lwp.ids-mannheim.de), a web portal for loanword dictionaries with German as the common donor language. The system described here is currently in use for excerpting data from a large range of historical and contemporary East Slavic monolingual dictionaries. The paper focuses on the tools that help in merging excerpts that are etymologically related to one and the same Polish etymon. The merging process involves eliminating redundancies and inconsistencies and, above all, mapping word senses of excerpted entries onto a common cross-language set of ‘metasenses’. This mapping may involve literally hundreds of excerpted East Slavic word senses, including quotations, for one ‘underlying’ Polish etymon.
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 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.
The workshop presents ATHEN 1 (Annotation and Text Highlighting Environment), an extensible desktop-based annotation environment which supports more than just regular annotation. Besides being a general purpose annotation environment, ATHEN supports indexing and querying support of your data as well as the ability to automatically preprocess your data with Meta information. It is especially suited for those who want to extend existing general purpose annotation tools by implementing their own custom features, which cannot be fulfilled by other available annotation environments. On the according gitlab, we provide online tutorials, which demonstrate the use of specific features of ATHEN
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.
This paper describes a rule-based approach to detect direct speech without the help of any quotation markers. As datasets fictional and non-fictional texts were used. Our evaluation shows that the results appear stable throughout different datasets in the fictional domain and are comparable to the results achieved in related work.
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.
Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society
(2020)
This paper proposes, implements and evaluates a novel, corpus-based approach for identifying categories indicative of the impact of research via a deductive (top-down, from theory to data) and an inductive (bottom-up, from data to theory) approach. The resulting categorization schemes differ in substance. Research outcomes are typically assessed by using bibliometric methods, such as citation counts and patterns, or alternative metrics, such as references to research in the media. Shortcomings with these methods are their inability to identify impact of research beyond academia (bibliometrics) and considering text-based impact indicators beyond those that capture attention (altmetrics). We address these limitations by leveraging a mixed-methods approach for eliciting impact categories from experts, project personnel (deductive) and texts (inductive). Using these categories, we label a corpus of project reports per category schema, and apply supervised machine learning to infer these categories from project reports. The classification results show that we can predict deductively and inductively derived impact categories with 76.39% and 78.81% accuracy (F1-score), respectively. Our approach can complement solutions from bibliometrics and scientometrics for assessing the impact of research and studying the scope and types of advancements transferred from academia to society.
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.
This paper presents C-WEP, the Collection of Writing Errors by Professionals Writers of German. It currently consists of 245 sentences with grammatical errors. All sentences are taken from published texts. All authors are professional writers with high skill levels with respect to German, the genres, and the topics. The purpose of this collection is to provide seeds for more sophisticated writing support tools as only a very small proportion of those errors can be detected by state-of-the-art checkers. C-WEP is annotated on various levels and freely available.
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 paper reports on an ongoing international project of compiling a freely accessible online Dictionary of German Loans in Polish Dialects. The dictionary will be the first comprehensive lexicographic compendium of its kind, serving as a complement to existing resources on German lexical loans in the literary or standard language. The empirical results obtained in the project will shed new light on the distribution of German loanwords among different dialects, also in comparison to the well-documented situation in written Polish. The dictionary will have a strong focus on the dialectal distribution of Polish dialectal variants for a given German etymon, accessible through interactive cartographic representations and corresponding search options. The editorial process is realized with dedicated collaborative web tools. The new resource will be published as an integrated part of an online information system for German lexical borrowings in other languages, the Lehnwortportal Deutsch, and is therefore highly cross-linked with other loanword dictionaries on Polish as well as Slavic and further European languages.
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 implementing a workflow for transcripts of spoken language following 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.
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.
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.
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.
This paper discusses how cognitive aspects can be incorporated into lexicographic meaning descriptions based on corpus-driven analysis. The new German Online dictionary “Paronyme − Dynamisch im Kontrast” is concerned with easily confused words such as effektiv/effizient, sensibel/sensitiv. It is currently in the process of being developed and it aims at adopting a more conceptual and encyclopedic approach to meaning. Contrastive entries emphasize usage, comparing conceptual categories and indicating the mapping of knowledge. Adaptable access to lexicographic details offers different perspectives on information, and authentic examples reflect prototypical structures.
Some of the cognitive features are demonstrated with the help of examples. Firstly, I will outline how patterns of usage imply conceptual categories as central ideas instead of sufficiently logical criteria of semantic distinction. In this way, linguistic findings correlate better with how users conceptualize language. Secondly, it is pointed out how collocates are family members and fillers in contexts. Thirdly, I will demonstrate how contextual structure and function are included by summarizing referential information. Details are drawn from corpus data; they are usage-based patterns illustrating conversational interaction and semantic negotiation in contemporary public discourse. Finally, I will show flexible consultation routines where the focus on structural knowledge changes.
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.
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.
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.
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.
The automatic recognition of idioms poses a challenging problem for NLP applications. Whereas native speakers can intuitively handle multiword expressions whose compositional meanings are hard to trace back to individual word semantics, there is still ample scope for improvement regarding computational approaches. We assume that idiomatic constructions can be characterized by gradual intensities of semantic non-compositionality, formal fixedness, and unusual usage context, and introduce a number of measures for these characteristics, comprising count-based and predictive collocation measures together with measures of context (un)similarity. We evaluate our approach on a manually labelled gold standard, derived from a corpus of German pop lyrics. To this end, we apply a Random Forest classifier to analyze the individual contribution of features for automatically detecting idioms, and study the trade-off between recall and precision. Finally, we evaluate the classifier on an independent dataset of idioms extracted from a list of Wikipedia idioms, achieving state-of-the art accuracy.
We discuss the modal uses of the Hausa exclusive particle sai (≈ only). We argue that the distribution of sai in modal environments provides evidence for the following claims on the composition of modal meaning that have been independently made in the literature: i) Future-oriented modality involves a prospective aspect operator that can be realized covertly in some languages (e.g. English, Kratzer 2012b) and overtly in others (e.g. Gitksan, Matthewson 2012, 2013). ii) Necessity interpretations arise from exhaustifying possibilities, i.e. an exhaustivity operator applying to existential modality (e.g. Kaufmann 2012 for the case of imperatives and Leffel 2012 for a relevant analysis of necessity meaning in Masalit). We show that future-oriented necessity in Hausa decomposes into EXH((PROSP)), with sai contributing exhaustivity.
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.
This contribution presents the procedure used in the Handbuch deutscher Kommunikationsverben and in its online version Kommunikationsverben in the lexicographical internet portal OWID to divide sets of semantically similar communication verbs into ever smaller sets of ever closer synonyms. Kommunikationsverben describes the meaning of communication verbs on two levels: a lexical level, represented in the dictionary entries and by sets of lexical features, and a conceptual level, represented by different types of situations referred to by specific types of verbs. The procedure starts at the conceptual level of meaning where verbs used to refer to the same specific situation type are grouped together. At the lexical level of meaning, the sets of verbs obtained from the first step are successively divided into smaller sets on the basis of the criteria of (i) identity of lexical meaning, (ii) identity of lexical features, and (iii) identity of contexts of usage. The stepwise procedure applied is shown to result in the creation of a semantic network for communication verbs.
We examine the new task of detecting derogatory compounds (e.g. curry muncher). Derogatory compounds are much more difficult to detect than derogatory unigrams (e.g. idiot) since they are more sparsely represented in lexical resources previously found effective for this task (e.g. Wiktionary). We propose an unsupervised classification approach that incorporates linguistic properties of compounds. It mostly depends on a simple distributional representation. We compare our approach against previously established methods proposed for extracting derogatory unigrams.
Automatic division of spoken language transcripts into sentence-like units is a challenging problem, caused by disfluencies, ungrammatical structures and the lack of punctuation. We present experiments on dividing up German spoken dialogues where we investigate the impact of task setup and data representation, encoding of context information as well as different model architectures for this task.
We discuss the impact of data bias on abusive language detection. We show that classification scores on popular datasets reported in previous work are much lower under realistic settings in which this bias is reduced. Such biases are most notably observed on datasets that are created by focused sampling instead of random sampling. Datasets with a higher proportion of implicit abuse are more affected than datasets with a lower proportion.
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.
Wolfgang von Kempelen's book "The Mechanism of Human Speech" from 1791 is a famous milestone in the history of speech communication research. It has an enormous relevance for the phonetic sciences and it marks an important turning point for the development of the (mechanical) speech synthesis. So far no English version of this work was available, which excludes many interested researchers. Access to the original versions in German and French is restricted for various reasons. For example the blackletter script of the German version is troublesome for most of today's readers. We report here on a new edition of Kempelen's book which unites a better readable German version and its English translation. It will now also be in a searchable electronic format and has been enriched with many commentaries, which aid in the understanding of details of the late 18th century that are little known or unknown to many researchers today.
German lexical items with similar or related morphological roots and similar meaning potential are easily confused by native speakers and language learners. These include so-called paronyms such as effektiv/effizient , sensitive/sensibel, formell/formal/förmlich . Although these are generally not regarded as synonyms, empirical studies suggest that in some cases items of a paronym set have undergone meaning change and developed synonymous notions. In other cases, they remain similar in meaning, but show subtle differences in definition and restrictions of usage. Whereas the treatment of synonyms has received attention from corpus-linguists (cf. Partington 1998; Taylor 2003), the subject of paronyms has not been revisited with empirical, data-driven methods neither in terms of semantic theory nor in terms of practical lexicography. As a consequence, we also need to search for suitable corpus methods for detailed semantic investigation. Lexicographically, some German paronyms have been documented in printed dictionaries (e.g. Müller 1973; Pollmann & Wolk 2010). However, there is no corpus-assisted reference guide describing paronyms empirically and enabling readers to find the correct contemporary usage. Therefore, solutions to some lexicographic challenges are required.
The sentiment polarity of an expression (whether it is perceived as positive, negative or neutral) can be influenced by a number of phenomena, foremost among them negation. Apart from closed-class negation words like no, not or without, negation can also be caused by so-called polarity shifters. These are content words, such as verbs, nouns or adjectives, that shift polarities in their opposite direction, e. g. abandoned in “abandoned hope” or alleviate in “alleviate pain”. Many polarity shifters can affect both positive and negative polar expressions, shifting them towards the opposing polarity. However, other shifters are restricted to a single shifting direction. Recoup shifts negative to positive in “recoup your losses”, but does not affect the positive polarity of fortune in “recoup a fortune”. Existing polarity shifter lexica only specify whether a word can, in general, cause shifting, but they do not specify when this is limited to one shifting direction. To address this issue we introduce a supervised classifier that determines the shifting direction of shifters. This classifier uses both resource-driven features, such as WordNet relations, and data-driven features like in-context polarity conflicts. Using this classifier we enhance the largest available polarity shifter lexicon.
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.
To improve grammatical function labelling for German, we augment the labelling component of a neural dependency parser with a decision history. We present different ways to encode the history, using different LSTM architectures, and show that our models yield significant improvements, resulting in a LAS for German that is close to the best result from the SPMRL 2014 shared task (without the reranker).
Unknown words are a challenge for any NLP task, including sentiment analysis. Here, we evaluate the extent to which sentiment polarity of complex words can be predicted based on their morphological make-up. We do this on German as it has very productive processes of derivation and compounding and many German hapax words, which are likely to bear sentiment, are morphologically complex. We present results of supervised classification experiments on new datasets with morphological parses and polarity annotations.
We propose to use abusive emojis, such as the “middle finger” or “face vomiting”, as a proxy for learning a lexicon of abusive words. Since it represents extralinguistic information, a single emoji can co-occur with different forms of explicitly abusive utterances. We show that our approach generates a lexicon that offers the same performance in cross-domain classification of abusive microposts as the most advanced lexicon induction method. Such an approach, in contrast, is dependent on manually annotated seed words and expensive lexical resources for bootstrapping (e.g. WordNet). We demonstrate that the same emojis can also be effectively used in languages other than English. Finally, we also show that emojis can be exploited for classifying mentions of ambiguous words, such as “fuck” and “bitch”, into generally abusive and just profane usages.
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.
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 2010, ISO published a standard for syntactic annotation, ISO 24615:2010 (SynAF). Back then, the document specified a comprehensive reference model for the representation of syntactic annotations, but no accompanying XML serialisation. ISO’s subcommittee on language resource management (ISO TC 37/SC 4) is working on making the SynAF serialisation ISOTiger an additional part of the standard. This contribution addresses the current state of development of ISOTiger, along with a number of open issues on which we are seeking community feedback in order to ensure that ISOTiger becomes a useful extension to the SynAF reference model.
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.
The German Historical Institute Washington (GHI) is in the development phase of German History Digital (GH-D), a transatlantic digital initiative to meet the scholarly needs of historians and their students facing new historiographical and technological challenges. In the proposed paper we will discuss the research goals, methodology, prototyping, and development strategy of GH-D as infrastructure to facilitate transnational historical knowledge co-creation for the large community of researchers and students already relying on digital resources of the GHI and for the growing constituency of citizen scholars.
This paper reports on an ongoing lexicographical project that investigates Polish loanwords from German that were further borrowed into the East Slavic languages Russian, Ukrainian, and Belorussian. The results will be published as three separate dictionaries in the Lehnwortportal Deutsch, a freely available web portal for loanword dictionaries having German as their common source language. On the database level, the portal models lexicographical data as a cross-resource directed acyclic graph of relations between individual words, including German ‘metalemmata’ as normalized representations of diasystemic variants of German etyma. Amongst other things, this technology makes it possible to use the web portal as an ‘inverted loanword dictionary’ to find loanwords in different languages borrowed from the same German etymon. The different possible pathways of German loanwords that went through Polish into the East Slavic languages can be represented directly as paths in the graph. A dedicated in-house dictionary editing software system assists lexicographers in producing and keeping track of these paths even in complex cases where, e.g, only a derivative of a German loanword in Polish has been borrowed into Russian. The paper concludes with some remarks on the particularities of the dictionary/portal access structure needed for presenting and searching borrowing chains.
Smooth turn-taking in conversation depends in part on speakers being able to communicate their intention to hold or cede the floor. Both prosodic and gestural cues have been shown to be used in this context. We investigate the interplay of pitch movements and hand gestures at locations at which speaker change becomes relevant, comparing their use in German and Swedish. We find that there are some shared functions of prosody and gesture with regard to turn-taking in the two languages, but that these shared functions appear to be mediated by the different phonological demands on pitch in the two languages.
We address the task of distinguishing implicitly abusive sentences on identity groups (“Muslims contaminate our planet”) from other group-related negative polar sentences (“Muslims despise terrorism”). Implicitly abusive language are utterances not conveyed by abusive words (e.g. “bimbo” or “scum”). So far, the detection of such utterances could not be properly addressed since existing datasets displaying a high degree of implicit abuse are fairly biased. Following the recently-proposed strategy to solve implicit abuse by separately addressing its different subtypes, we present a new focused and less biased dataset that consists of the subtype of atomic negative sentences about identity groups. For that task, we model components that each address one facet of such implicit abuse, i.e. depiction as perpetrators, aspectual classification and non-conformist views. The approach generalizes across different identity groups and languages.
We examine the task of detecting implicitly abusive comparisons (e.g. “Your hair looks like you have been electrocuted”). Implicitly abusive comparisons are abusive comparisons in which abusive words (e.g. “dumbass” or “scum”) are absent. We detail the process of creating a novel dataset for this task via crowdsourcing that includes several measures to obtain a sufficiently representative and unbiased set of comparisons. We also present classification experiments that include a range of linguistic features that help us better understand the mechanisms underlying abusive comparisons.
Implicitly abusive language – What does it actually look like and why are we not getting there?
(2021)
Abusive language detection is an emerging field in natural language processing which has received a large amount of attention recently. Still the success of automatic detection is limited. Particularly, the detection of implicitly abusive language, i.e. abusive language that is not conveyed by abusive words (e.g. dumbass or scum), is not working well. In this position paper, we explain why existing datasets make learning implicit abuse difficult and what needs to be changed in the design of such datasets. Arguing for a divide-and-conquer strategy, we present a list of subtypes of implicitly abusive language and formulate research tasks and questions for future research.
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 CLARIN Concept Registry (CCR) is the common semantic ground for most CMDI-based profiles to describe language-related resources in the CLARIN universe. While the CCR supports semantic interoperability within this universe, it does not extend beyond it. The flexibility of CMDI, however, allows users to use other term or concept registries when defining their metadata components. In this paper, we describe our use of schema.org, a light ontology used by many parties across disciplines.
We address the detection of abusive words. The task is to identify such words among a set of negative polar expressions. We propose novel features employing information from both corpora and lexical resources. These features are calibrated on a small manually annotated base lexicon which we use to produce a large lexicon. We show that the word-level information we learn cannot be equally derived from a large dataset of annotated microposts. We demonstrate the effectiveness of our (domain-independent) lexicon in the crossdomain detection of abusive microposts.
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.
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.
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).
There are a number of recent replicas of Wolfgang von Kempelen's speaking machine. Although all of them are explicitly based on Kempelen's own description nearly none of them are identical in construction and sound. In this paper we want to illustrate some of these differences and their reasons for five replicas built by ourselves.
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.
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).
This paper presents the Lehnwortportal Deutsch, a new, freely accessible publication platform for resources on German lexical borrowings in other languages, to be launched in the second half of 2022. The system will host digital-native sources as well as existing, digitized paper dictionaries on loanwords, initially for some 15 recipient languages. All resources remain accessible as individual standalone dictionaries; in addition, data on words (etyma, loanwords etc.) together with their senses and relations to each other is represented as a cross-resource network in a graph database, with careful distinction between information present in the original sources and the curated portal network data resulting from matching and merging information on, e. g., lexical units appearing in multiple dictionaries. Special tooling is available for manually creating graphs from dictionary entries during digitization and for editing and augmenting the graph database. The user interface allows users to browse individual dictionaries, navigate through the underlying graph and ‘click together’ complex queries on borrowing constellations in the graph in an intuitive way. The web application will be available as open source.
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.
Making 1:n explorable: a search interface for the ZAS database of clause-embedding predicates
(2017)
We introduce a recently published corpus-based database of German clause-embedding predicates and present an innovative web application for exploring it. The application displays the predicates and the corpus examples for these predicates in two separate tables that can be browsed and searched in real time. While familiar web interface paradigms make it easy for users to get started, the data presentation and the interactive advanced search components for the two tables are designed to accommodate remarkably complex query needs without the need for resorting to a dedicated query language or a more specialized tool. The 1:n relationship between predicates and their examples is exploited in the two tables in that, e.g. the predicate table also shows, for each predicate and each example attribute, all values that occur in the examples for this predicate. An easy-to-use visual query builder for arbitrary Boolean combinations of search criteria can optionally be displayed to pre-filter the underlying data presented in both tables. Several options for altering quantifier scope can be activated with simple checkboxes and considerably widen the space of searchable constellations.
This paper presents an algorithm and an implementation for efficient tokenization of texts of space-delimited languages based on a deterministic finite state automaton. Two representations of the underlying data structure are presented and a model implementation for German is compared with state-of-the-art approaches. The presented solution is faster than other tools while maintaining comparable quality.
Metadata provides important information relevant both to finding and understanding corpus data. Meaningful linguistic data requires both reasonable annotations and documentation of these annotations. This documentation is part of the metadata of a dataset. While corpus documentation has often been provided in the form of accompanying publications, machinereadable metadata, both containing the bibliographic information and documenting the corpus data, has many advantages. Metadata standards allow for the development of common tools and interfaces. In this paper I want to add a new perspective from an archive’s point of view and look at the metadata provided for four learner corpora and discuss the suitability of established standards for machine-readable metadata. I am are aware that there is ongoing work towards metadata standards for learner corpora. However, I would like to keep the discussion going and add another point of view: increasing findability and reusability of learner corpora in an archiving context.
Machine learning methods offer a great potential to automatically investigate large amounts of data in the humanities. Our contribution to the workshop reports about ongoing work in the BMBF project KobRA (http://www.kobra.tu-dortmund.de) where we apply machine learning methods to the analysis of big corpora in language-focused research of computer-mediated communication (CMC). At the workshop, we will discuss first results from training a Support Vector Machine (SVM) for the classification of selected linguistic features in talk pages of the German Wikipedia corpus in DeReKo provided by the IDS Mannheim. We will investigate different representations of the data to integrate complex syntactic and semantic information for the SVM. The results shall foster both corpus-based research of CMC and the annotation of linguistic features in CMC corpora.
The paper at hand discusses productivity in German compound formation – as a case of morphological variation – from a lexeme-based synchronic perspective. In particular, we focus on groups of compounds with semantically closely related head words, e.g., compounds denoting colors.
Our approach is characterized by a qualitative as well as a quantitative perspective on productivity. Taking the properties of the head lexeme as a starting point and applying corpus-based statistical methods, we try to gain new insights into compound formation, especially into potential factors which govern their productivity. In a first step, we determine the productivity of compounds on the basis of current productivity measures and data from a large corpus of German. In a second step, we try to systematically explain observable differences in productivity.
The approach presented here is one of the first attempts to apply the concept of productivity, which has been predominantly used in the domain of derivation, to compounding. Since compounding is a dominant factor for the expansion of the German lexicon, we assume that our investigation also sheds an important light on the dynamics of the lexicon.
New exceptions for Text and Data Mining and their possible impact on the CLARIN infrastructure
(2018)
The proposed paper discusses new exceptions for Text and Data Mining that have recently been adopted in some EU Member States, and probably will soon be adopted also at the EU level. These exceptions are of great significance for language scientists, as they exempt those who compile corpora from the obligation to obtain authorisation from rightholders. However, corpora compiled on the basis of such exceptions cannot be freely shared, which in a long run may have serious consequences for Open Science and the functioning of research infrastructure such as CLARIN ERIC.
Newspapers became extremely popular in Germany during the 18th and 19th century, and thus increasingly influential for modern German. However, due to the lack of digitized historical newspaper corpora for German, this influence could not be analyzed systematically. In this paper, we introduce the Mannheim Corpus of Digital Newspapers and Magazines, which in its current release comprises 21 newspapers and magazines from the 18th and 19th century. With over 4.1 Mio tokens in about 650 volumes it currently constitutes the largest historical corpus dedicated to newspapers in German. We briefly discuss the prospect of the corpus for analyzing the evolution of news as a genre in its own right and the influence of contextual parameters such as region and register on the language of news. We then focus on one historically influential aspect of newspapers – their role in disseminating foreign words in German. Our preliminary quantitative results indeed indicate that newspapers use foreign words significantly more frequently than other genres, in particular belles lettres.
Open Science and language data: Expectations vs. reality. The role of research data infrastructures
(2023)
Language data are essential for any scientific endeavor. However, unlike numerical data, language data are often protected by copyright, as they easily meet the threshold of originality. The role of research infrastructures (such CLARIN, DARIAH, and Text+) is to bridge the gap between uses allowed by statutory exceptions and the requirements of Open Science. This is achieved on the one hand by sharing language data produced by research organisations with the widest possible circle of persons, and on the other by mutualizing efforts towards copyright clearance and appropriate licensing of datasets.
We present the second edition of the GermEval Shared Task on the Identification of Offensive Language. This shared task deals with the classification of German tweets from Twitter. Two subtasks were continued from the first edition, namely a coarse-grained binary classification task and a fine-grained multi-class classification task. As a novel subtask, we introduce the classification of offensive tweets as explicit or implicit.
The shared task had 13 participating groups submitting 28 runs for the coarse-grained
task, another 28 runs for the fine-grained task, and 17 runs for the implicit-explicit
task.
We evaluate the results of the systems submitted to the shared task. The shared task homepage can be found at https://projects.fzai.h-da.de/iggsa/
Polish żeby under negation
(2021)
The paper addresses two patterns in the distribution of complement clauses headed by the complementizer żeby in Polish related to the presence of sentential negation. It is argued that żeby-clauses with an obligatory negation in the matrix clause, licensed by epistemic verbs, can be treated in terms of negative polarity, with żeby defined as an n-word. Structures with żeby-clauses and an obligatory negation in the embedded clause, licensed by verbs of fear, are argued to be an instance of negative complementation, with żeby specified as a negative complementizer. A uniform lexicalist analysis within the framework of HPSG is provided, employing tools developed to account for Negative Concord in Polish.
In order to develop its full potential, global communication needs linguistic support systems such as Machine Translation (MT). In the past decade, free online MT tools have become available to the general public, and the quality of their output is increasing. However, the use of such tools may entail various legal implications, especially as far as processing of personal data is concerned. This is even more evident if we take into account that their business model is largely based on providing translation in exchange for data, which can subsequently be used to improve the translation model, but also for commercial purposes. The purpose of this paper is to examine how free online MT tools fit in the European data protection framework, harmonised by the EU Data Protection Directive. The perspectives of both the user and the MT service provider are taken into account.
Contents:
1. Michal Křen: Recent Developments in the Czech National Corpus, S. 1
2. Dan Tufiş, Verginica Barbu Mititelu, Elena Irimia, Stefan Dumitrescu, Tiberiu Boros, Horia Nicolai Teodorescu: CoRoLa Starts Blooming – An update on the Reference Corpus of Contemporary Romanian Language, S. 5
3. Sebastian Buschjäger, Lukas Pfahler, Katharina Morik: Discovering Subtle Word Relations in Large German Corpora, S. 11
4. Johannes Graën, Simon Clematide: Challenges in the Alignment, Management and Exploitation of Large and Richly Annotated Multi-Parallel Corpora, S. 15
5. Stefan Evert, Andrew Hardie: Ziggurat: A new data model and indexing format for large annotated text corpora, S. 21
6. Roland Schäfer: Processing and querying large web corpora with the COW14 architecture, S. 28
7. Jochen Tiepmar: Release of the MySQL-based implementation of the CTS protocol, S. 35