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This paper reports on the efforts of twelve national teams in building the International Comparable Corpus (ICC; https://korpus.cz/icc) that will contain highly comparable datasets of spoken, written and electronic registers. The languages currently covered are Czech, Finnish, French, German, Irish, Italian, Norwegian, Polish, Slovak, Swedish and, more recently, Chinese, as well as English, which is considered to be the pivot language. The goal of the project is to provide much-needed data for contrastive corpus-based linguistics. The ICC corpus is committed to the idea of re-using existing multilingual resources as much as possible and the design is modelled, with various adjustments, on the International Corpus of English (ICE). As such, ICC will contain approximately the same balance of forty percent of written language and 60 percent of spoken language distributed across 27 different text types and contexts. A number of issues encountered by the project teams are discussed, ranging from copyright and data sustainability to technical advances in data distribution.
Dieser Beitrag widmet sich der Beschreibung des Korpus Deutsch in Namibia (DNam), das über die Datenbank für Gesprochenes Deutsch (DGD) frei zugänglich ist. Bei diesem Korpus handelt es sich um eine neue digitale Ressource, die den Sprachgebrauch der deutschsprachigen Minderheit in Namibia sowie die zugehörigen Spracheinstellungen umfassend und systematisch dokumentiert. Wir beschreiben die Datenerhebung und die dabei angewandten Methoden (freie Gespräche, „Sprachsituationen“, semi-strukturierte Interviews), die Datenaufbereitung inklusive Transkription, Normalisierung und Tagging sowie die Eigenschaften des verfügbaren Korpus (Umfang, verfügbare Metadaten usw.) und einige grundlegende Funktionalitäten im Rahmen der DGD. Erste Forschungsergebnisse, die mithilfe der neuen Ressource erzielt wurden, veranschaulichen die vielseitige Nutzbarkeit des Korpus für Fragestellungen aus den Bereichen Kontakt-, Variations-
und Soziolinguistik.
Within cognitive linguistics, there is an increasing awareness that the study of linguistic phenomena needs to be grounded in usage. Ideally, research in cognitive linguistics should be based on authentic language use, its results should be replicable, and its claims falsifiable. Consequently, more and more studies now turn to corpora as a source of data. While corpus-based methodologies have increased in sophistication, the use of corpus data is also associated with a number of unresolved problems. The study of cognition through off-line linguistic data is, arguably, indirect, even if such data fulfils desirable qualities such as being natural, representative and plentiful. Several topics in this context stand out as particularly pressing issues. This discussion note addresses (1) converging evidence from corpora and experimentation, (2) whether corpora mirror psychological reality, (3) the theoretical value of corpus linguistic studies of ‘alternations’, (4) the relation of corpus linguistics and grammaticality judgments, and, lastly, (5) the nature of explanations in cognitive corpus linguistics. We do not claim to resolve these issues nor to cover all possible angles; instead, we strongly encourage reactions and further discussion.
How (and when) do speakers generalise from memorised exemplars of a construction to a productive schema? The present paper presents a novel take on this issue by offering a corpus-based approach to semantic extension processes. Focusing on clusters of German ADJ N expressions involving the heavily polysemous adjective tief ‚deep’, it is shown that type frequency (a commonly used measure of productivity) needs to be relativised to distinct semantic classes within the overall usage spectrum of a given construction in order to predict the occurrence of novel types within a particular region of this spectrum. Some methodological and theoretical implications for usage-based linguistic model building are considered.
Linguistic corpora have been annotated by means of SGML-based markup languages for almost 20 years. We can, very roughly, differentiate between three distinct evolutionary stages of markup technologies. (1)Originally, single SGML tree-based document instances were deemed sufficient for the representation of linguistic structures. (2) Linguists began to realize that alternatives and extensions to the traditional model are needed. Formalisms such as, for example, NITE were proposed: the NITE Object Model (NOM) consists of multi-rooted trees. (3) We are now on the threshold of the third evolutionary stage: even NITE's very flexible approach is not suited for all linguistic purposes. As some structures, such as these, cannot be modeled by multi-rooted trees, an even more flexible approach is needed in order to provide a generic annotation format that is able to represent genuinely arbitrary linguistic data structures.
Ziel dieses Projekts ist es, Sprachdaten so nah wie möglich am Jetzt zu erheben und analysierbar zu machen. Wir möchten, dass möglichst viele Menschen, nicht nur Sprachwissenschaftlerinnen und Sprachwissenschaftler, in die Lage versetzt werden, Sprachdaten zu explorieren und zu nutzen. Hierzu erheben wir ein Korpus, d. h. eine aufbereitete Sammlung von Sprachdaten von RSS-Feeds deutschsprachiger Onlinequellen. Wir zeichnen die Entwicklung der Analysewerkzeuge von einem Prototyp hin zur aktuellen Form der Anwendung nach, die eine komplette Reimplementierung darstellt. Dabei gehen wir auf die Architektur, einige Analysebeispiele sowie Erweiterungsmöglichkeiten ein. Fragen der Skalierbarkeit und Performanz stehen dabei im Mittelpunkt. Unsere Darstellungen lassen sich daher auf andere Data-Science-Projekte verallgemeinern.
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.
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divided into 16 parts based on 16 corpus folds. We describe how the dataset was created and structured. By evaluating the distribution over the 16 folds, we show that it is possible to work with a subset of the folds in many use cases (e.g., to save computational resources). In a case study, we investigate the growth of vocabulary (as well as the number of hapax legomena) as an increasing number of folds are included in the analysis. We cross-combine this with the various cleaning stages of the dataset. We also give some guidance in the form of Python, R, and Stata markdown scripts on how to work with the resource.
Based on the privative derivational suffix -los, we test statements found in the literature on word formation using a – at least in this field – novel empirical basis: a list of affective-emotional ratings of base nouns and associated -los derivations. In addition to a frequency analysis based on the German Reference Corpus, we show that, in general, emotional polarity (so-called valence, positive vs. negative emotions) is reversed by suffixation with -los. This change is stronger for more polarized base nouns. The perceived intensity of emotion (so-called arousal) is generally lower for -los derivations than for base nouns. Finally, to capture the results theoretically, we propose a prototypical -los construction in the framework of Construction Morphology.
Juristische Texte sind schwer zu verstehen, insbesondere – aber nicht nur – für juristische Laien. Dieser Band beleuchtet diese These ausgehend von linguistischen Verständlichkeitsmodellen und kognitionswissenschaftlichen Modellen der menschlichen Textverarbeitung. Anhand von Aufzeichnungen von Blickbewegungen beim Lesen, einem sogenannten Lesekorpus, werden umfangreiche statistische Modelle berechnet. Diese geben Auskunft über Fragen psycholinguistischer Grundlagenforschung auf der Wort-, Satz- und Textebene. Ferner wird untersucht, wie sich Reformulierungen auf den Verstehensprozess auswirken. Dabei stehen bekannte Komplexitätsmarker deutscher juristischer Texte im Fokus: Nominalisierungen, komplexe Nominalphrasen und syntaktisch komplexe Texte.
We describe a general two-stage procedure for re-using a custom corpus for spoken language system development involving a transformation from character-based markup to XML, and DSSSL stylesheet-driven XML markup enhancement with multiple lexical tag trees. The procedure was used to generate a fully tagged corpus; alternatively with greater economy of computing resources, it can be employed as a parametrised ‘tagging on demand’ filter. The implementation will shortly be released as a public resource together with the corpus (German spoken dialogue, about 500k word form tokens) and lexicon (about 75k word form types).
The actual or anticipated impact of research projects can be documented in scientific publications and project reports. While project reports are available at varying level of accessibility, they might be rarely used or shared outside of academia. Moreover, a connection between outcomes of actual research project and potential secondary use might not be explicated in a project report. This paper outlines two methods for classifying and extracting the impact of publicly funded research projects. The first method is concerned with identifying impact categories and assigning these categories to research projects and their reports by extension by using subject matter experts; not considering the content of research reports. This process resulted in a classification schema that we describe in this paper. With the second method which is still work in progress, impact categories are extracted from the actual text data.
Overlap in markup occurs where some markup structures do not nest, such as where the structural division of the text into lists, sections, etc., differs from the syntactic division of the text into sentences and phrases. The Multiple Annotation solution to this problem (redundant encoding in multiple forms) has many advantages: it is based on XML, the modeling of alternative annotations is possible, each level can be viewed separately, and new levels can be added at any time. But it has the significant disadvantage of independence of the separate files. These multiply annotated files can be regarded as an interrelated unit, with the text serving as the implicit link. Two representations of the information contained in the multiple files (one in Prolog and one in XML) can be programmatically derived and used together for editing, for inference, or for unification of the multiply annotated documents.
Die zentrale Aufgabenstellung des Verbundprojektes TextTransfer (Pilot) war eine Machbarkeitsprüfung für die Entwicklung eines Text-Mining-Verfahrens, mit dem Forschungsergebnisse automatisiert auf Hinweise zu Transfer- und Impactpotenzialen untersucht werden können. Das vom Projektkoordinator IDS verantwortete Teilprojekt konzentrierte sich dabei auf die Entwicklung der methodischen Grundlagen, während der Projektpartner TIB vornehmlich für die Bereitstellung eines geeigneten Datensatzes verantwortlich war. Solchen automatisierten Verfahren liegen zumeist textbasierte Daten als physisches Manifest wissenschaftlicher Erkenntnisse zugrunde, die im Falle von TextTransfer (Pilot) als empirische Grundlage herangezogen wurden. Das im Verbund zur Anwendung gebrachte maschinelle Lernverfahren stützte sich ausschließlich auf deutschsprachige Projektendberichte öffentlich geförderter Forschung. Diese Textgattung eignet sich insbesondere hinsichtlich ihrer öffentlichen Verfügbarkeit bei zuständigen Gedächtnisorganisationen und aufgrund ihrer im Vergleich zu anderen Formaten wissenschaftlicher Publikation relativen strukturellen wie sprachlichen Homogenität. TextTransfer (Pilot) ging daher grundsätzlich von der Annahme struktureller bzw. sprachlicher Ähnlichkeit in Berichtstexten aus, bei denen der Nachweis tatsächlich erfolgten Transfers zu erbringen war. Im Folgenden wird in diesen Fällen von Texten bzw. textgebundenen Forschungsergebnissen mit Transfer- und Impactpotenzial gesprochen werden. Es wurde ferner postuliert, dass sich diese Indizien von sprachlichen Eigenschaften in Texten zu Projekten ohne nachzuweisenden bzw. ggf. auch niemals erfolgtem, aber potenziell möglichem Transfer oder Impact unterscheiden lassen. Mit einer Verifizierung dieser Annahmen war es möglich, Transfer- oder Impactwahrscheinlichkeiten in großen Mengen von Berichtsdaten ohne eingehende Lektüre zu prognostizieren.
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.
A syntax-based scheme for the annotation and segmentation of German spoken language interactions
(2018)
Unlike corpora of written language where segmentation can mainly be derived from orthographic punctuation marks, the basis for segmenting spoken language corpora is not predetermined by the primary data, but rather has to be established by the corpus compilers. This impedes consistent querying and visualization of such data. Several ways of segmenting have been proposed,
some of which are based on syntax. In this study, we developed and evaluated annotation and segmentation guidelines in reference to the topological field model for German. We can show that these guidelines are used consistently across annotators. We also investigated the influence of various interactional settings with a rather simple measure, the word-count per segment and unit-type. We observed that the word count and the distribution of each unit type differ in varying interactional settings and that our developed segmentation and annotation guidelines are used consistently across annotators. In conclusion, our syntax-based segmentations reflect interactional properties that are intrinsic to the social interactions that participants are involved in. This can be used for further analysis of social interaction and opens the possibility for automatic segmentation of transcripts.