Korpuslinguistik
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The project Referenzkorpus Altdeutsch (‘Old German Reference Corpus’) aims to es- tablish a deeply-annotated text corpus of all extant Old German texts. As the automated part-of-speech and morphological pre-annotation is amended by hand, a quality control system for the results seems a desirable objective. To this end, standardized inflectional forms, generated using the morphological information, are compared with the attested word forms. Their creation is described by way of example for the Old High German part of the corpus. As is shown, in a few cases, some features of the attested word forms are also required in order to determine as exactly as possible the shape of the inflected lemma form to be created.
The availability of electronic corpora of historical stages of languages has been wel- comed as possibly attenuating the inherent problem of diachronic linguistics, i.e. that we only have access to what has chanced to come down to us - the problem which was memorably named by Labov (1992) as one of “Bad Data”. However, such corpora can only give us access to an increased amount ot historical material and this can essentially still only be a partial and possibly distorted picture of the actual language at a particular period of history. Corpora can be improved by taking a more representative sample of extant texts if these are available (as they are in significant number for periods after the invention of printing). But, as examples from the recently compiled GerManC corpus of seventeenth and eighteenth century German show, the evidence from such corpora can still fail to yield definitive answers to our questions about earlier stages of a language. The data still require expert interpretation, and it is important to be realistic about what can legitimately be expected from an electronic historical corpus.
Multi-faceted alignment. Toward automatic detection of textual similarity in Gospel-derived texts
(2015)
Ancient Germanic Bible-derived texts stand in as test material for producing computational means for automatically determining where textual contamination and linguistic interference have influenced the translation process. This paper reports on the results of research efforts that produced a text corpus; a method for decomposing the texts involved into smaller, more directly comparable thematically-related chunks; a database of relationships between these chunks; and a user-interface allowing for searches based on various referential criteria. Finally, the state of the product at the end of the project is discussed, namely as it was handed over to another researcher who has extended it to automatically find semantic and syntactic similarities within comparable chunks.
In this paper we present some preliminary considerations concerning the possibility of automatic parsing an annotated corpus for N-N compounds. This should in prin- ciple be possible at least for relational and stereotype compounds, if the lemmatization of the corpus connects the lemmata with lexical entries as described in Höhle (1982). These lexical entries then supply the necessary information about the argument structure of a relational noun or about the stereotypical purpose associated with the noun’s referent which can be used to establish a relation between the first and the head constituent of the compound.
The relative order of dative and accusative objects in older German is less free than it is today. The reason for this could be that speakers of the direct predecessor of Old High German organized the referents according to the Thematic Hierarchy. If one applies a Case Hierarchy Nom>Acc>Dat to this, the order Nom - Dat - Acc falls out. It becomes apparent that the status of the Thematic Hierarchy is not a factor governing underlying word order, but a factor inducing scrambling. Arguments from binding theory, whose validity is discussed, indicate that the underlying order is ‘accusative before dative’
In this article, we provide an insight into the development and application of a corpus-lexicographic tool for finding neologisms that are not yet listed in German dictionaries. As a starting point, we used the words listed in a glossary of German neologisms surrounding the COVID-19 pandemic. These words are lemma candidates for a new dictionary on COVID-19 discourse in German. They also provided the database used to develop and test the NeoRate tool. We report on the lexicographic work in our dictionary project, the design and functionalities of NeoRate, and describe the first test results with the tool, in particular with regard to previously unregistered words. Finally, we discuss further development of the tool and its possible applications.
This paper presents the IVK-Ler corpus, a longitudinal, annotated learner corpus of weekly writings produced by a group of 18 adolescents in a preparatory class. The corpus consists of 117 student texts collected between 2020 and 2021 and has a structure layered by student and text number. It includes metadata that enables researchers to analyze and track individual student progress in terms of syntactic competence and literacy. The annotation schema, manual and automatic annotation processes, and corpus representation are described in detail. The corpus currently includes target hypotheses and gold standard part-of-speech tags. Future work could include additional annotation layers for topological fields and dependency relations, as well as semantic and discourse annotations to make the corpus usable for tasks beyond syntactic evaluations.
This article details the process of creating the Nottinghamer Korpus deutscher YouTube-Sprache ('The Nottingham German YouTube Language Corpus' - or NottDeuYTSch corpus) and outlines potential research opportunities. The corpus was compiled to analyse the online language produced by young German-speakers and offers significant opportunity for in-depth research across several linguistic fields including lexis, morphology, syntax, orthography, and conversational and discursive analysis. The NottDeuYTSch corpus contains over 33 million words taken from approximately 3 million YouTube comments from videos published between 2008 to 2018 targeted at a young, German-speaking demographic and represent an authentic language snapshot of young German speakers. The corpus was proportionally sampled based on video category and year from a database of 112 popular German-speaking YouTube channels in the DACH region for optimal representativeness and balance and contains a considerable amount of associated metadata for each comment that enable further longitudinal cross-sectional analyses. The NottDeuYTSch corpus is available for analysis as part of the German Reference Corpus (DeReKo).
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.
In this paper, we present an overview of freely available web applications providing online access to spoken language corpora. We explore and discuss various solutions with which the corpus providers and corpus platform developers address the needs of researchers who are working with spoken language. The paper aims to contribute to the long-overdue exchange and discussion of methods and best practices in the design of online access to spoken language corpora.