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  1. Testing the relationship between word length, frequency, and predictability based on the German Reference Corpus
    Autor*in: Koplenig, Alexander ; Kupietz, Marc ; Wolfer, Sascha
    Erschienen: 2022
    Verlag:  Hoboken : Wiley ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS) [Zweitveröffentlichung]

    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... mehr

     

    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.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einer Zeitschrift
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Wortlänge; Worthäufigkeit; Vorhersagbarkeit; Korpus; Informationsgehalt; Deutsch; Informationstheorie
    Lizenz:

    rightsstatements.org/page/InC/1.0/ ; info:eu-repo/semantics/openAccess
  2. Count-based and predictive language models for exploring DeReKo
    Autor*in: Fankhauser, Peter ; Kupietz, Marc
    Erschienen: 2022
    Verlag:  Paris : European Language Resources Association (ELRA) ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    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... mehr

     

    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.

     
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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Korpus; Deutsch; Kollokation; Syntagma; Assoziationsmaß; Paradigma
    Lizenz:

    creativecommons.org/licenses/by-nc/4.0/ ; info:eu-repo/semantics/openAccess
  3. Proceedings of the LREC 2022 Workshop on Challenges in the Management of Large Corpora (CMLC-10 2022). Marseille, 20 June 2022
    Autor*in: Bański, Piotr ; Barbaresi, Adrien ; Clematide, Simon ; Kupietz, Marc ; Lüngen, Harald
    Erschienen: 2022
    Verlag:  Paris : European Language Resources Association (ELRA) ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    Contents: 1. Vasile Pais, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Roxana Micu and Carol Luca Gasan: Challenges in Creating a Representative Corpus of Romanian Micro-Blogging Text. Pp. 1-7 2. Modest von Korff: Exhaustive Indexing of... mehr

     

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

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Korpus; Daten; Datenmanagement; Datensammlung; Datenanalyse; Datensatz; Datenqualität
    Lizenz:

    creativecommons.org/licenses/by-nc/4.0/ ; info:eu-repo/semantics/openAccess
  4. Tokenizing on scale. Preprocessing large text corpora on the lexical and sentence level
    Autor*in: Diewald, Nils ; Kupietz, Marc ; Lüngen, Harald
    Erschienen: 2022
    Verlag:  Mannheim : IDS-Verlag

    When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research... mehr

     

    When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state-ofthe-art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Englisch, Altenglisch (420)
    Schlagworte: Korpus; Software; Automatische Sprachanalyse; Daten; Deutsch
    Lizenz:

    creativecommons.org/licenses/by-sa/3.0/de/deed.de ; info:eu-repo/semantics/openAccess
  5. Tokenizing on scale. Preprocessing large text corpora on the lexical and sentence level
    Autor*in: Diewald, Nils ; Kupietz, Marc ; Lüngen, Harald
    Erschienen: 2022
    Verlag:  Mannheim : IDS-Verlag ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research... mehr

     

    When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state of the art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Englisch, Altenglisch (420)
    Schlagworte: Korpus
    Lizenz:

    creativecommons.org/licenses/by-sa/4.0/deed.de ; info:eu-repo/semantics/openAccess
  6. Building paths to corpus data. A multi-level least effort and maximum return approach
    Autor*in: Kupietz, Marc ; Diewald, Nils ; Margaretha, Eliza
    Erschienen: 2022
    Verlag:  Berlin/Boston : de Gruyter ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    Enabling appropriate access to linguistic research data, both for many researchers and for innovative research applications, is a challenging task. In this chapter, we describe how we address this challenge in the context of the German Reference... mehr

     

    Enabling appropriate access to linguistic research data, both for many researchers and for innovative research applications, is a challenging task. In this chapter, we describe how we address this challenge in the context of the German Reference Corpus DeReKo and the corpus analysis platform KorAP. The core of our approach, which is based on and tightly integrated into the CLARIN infrastructure, is to offer access at different levels. The graduated access levels make it possible to find a low-loss compromise between the possibilities opened up and the costs incurred by users and providers for each individual use case, so that, viewed over many applications, the ratio between effort and results achieved can be effectively optimized. We also report on experiences with the current state of this approach.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Sprachdaten; Deutsches Referenzkorpus (DeReKo); Korpus; Technische Infrastruktur; Nachhaltigkeit
    Lizenz:

    creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/openAccess