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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.
We present a simple tool for extracting text and markup information from printouts of (not only) scientific documents. While the heavy-lifting OCR is done by off-the-shelf tesseract, our focus is on detection, extraction, and basic categorization of color-highlighted text sections, as well as on providing a framework for downstream processing of extraction results. The tool can be useful for document analysis tasks that must, or benefit from being able to, use printed paper.
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.
The proposed contribution will shed light on current and future challenges on legal and ethical questions in research data infrastructures. The authors of the proposal will present the work of NFDI’s section on Ethical, Legal and Social Aspects (hereinafter: ELSA), whose aim is to facilitate cross-disciplinary cooperation between the NFDI consortia in the relevant areas of management and re-use of research data.
This paper describes general requirements for evaluating and documenting NLP tools with a focus on morphological analysers and the design of a Gold Standard. It is argued that any evaluation must be measurable and documentation thereof must be made accessible for any user of the tool. The documentation must be of a kind that it enables the user to compare different tools offering the same service, hence the descriptions must contain measurable values. A Gold Standard presents a vital part of any measurable evaluation process, therefore, the corpus-based design of a Gold Standard, its creation and problems that occur are reported upon here. Our project concentrates on SMOR, a morphological analyser for German that is to be offered as a web-service. We not only utilize this analyser for designing the Gold Standard, but also evaluate the tool itself at the same time. Note that the project is ongoing, therefore, we cannot present final results.
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.
Corpus-based identification and disambiguation of reading indicators for German nominalizations
(2010)
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must be made aware of ambiguities. Therefore, given an extraction task, all relevant ambiguities must be identified. To resolve these ambiguities, contextual data responsible for one or another reading is to be considered. In the context of our present work, German -ung-nominalizations and their sortal readings are under examination. A number of these nominalizations may be read as an event or a result, depending on the semantic group they belong to. Here, we concentrate on nominalizations of verbs of saying (henceforth: "verba dicendi"), identify their context partners and their influence on the sortal reading of the nominalizations in question. We present a tool which calculates the sortal reading of such nominalizations and thus may improve not only corpus extraction, but also e.g. machine translation. Lastly, we describe successful attempts to identify the correct sortal reading, conclusions and future work.
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
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.