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Data-Driven Identification of German Phrasal Compounds

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Text, Speech, and Dialogue (TSD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10415))

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Abstract

We present a method to identify and document a phenomenon on which there is very little empirical data: German phrasal compounds occurring in the form of as a single token (without punctuation between their components). Relying on linguistic criteria, our approach implies to have an operational notion of compounds which can be systematically applied as well as (web) corpora which are large and diverse enough to contain rarely seen phenomena. The method is based on word segmentation and morphological analysis, it takes advantage of a data-driven learning process. Our results show that coarse-grained identification of phrasal compounds is best performed with empirical data, whereas fine-grained detection could be improved with a combination of rule-based and frequency-based word lists. Along with the characteristics of web texts, the orthographic realizations seem to be linked to the degree of expressivity.

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Notes

  1. 1.

    “One-should-be-able-to-talk-about-everything motto”, “I-like-you-policy”. All examples appear in their original graphic realization, as found in previous studies [19] and billion-token web corpora [5, 6].

  2. 2.

    One PC-type defined is not captured by our automatic detection: Word formations whose non-head consists of not explicitly coordinated NPs, e.g. Frage-Antwort-Stunde, cf. p. 194 f.

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Author information

Authors and Affiliations

  1. Zentrum Sprache, Berlin-Brandenburg Academy of Sciences, Jägerstraße 22/23, 10117, Berlin, Germany

    Adrien Barbaresi

  2. Lexical Department, Institute for the German Language, R5, 6-13, 68161, Mannheim, Germany

    Katrin Hein

  3. Academy Corpora, Austrian Academy of Sciences, Sonnenfelsgasse 19, 1010, Vienna, Austria

    Adrien Barbaresi

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  1. Adrien Barbaresi
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  2. Katrin Hein
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Correspondence to Adrien Barbaresi .

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Editors and Affiliations

  1. University of West Bohemia, Pilsen, Czech Republic

    Kamil Ekštein

  2. University of West Bohemia, Pilsen, Czech Republic

    Václav Matoušek

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Barbaresi, A., Hein, K. (2017). Data-Driven Identification of German Phrasal Compounds. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_22

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  • DOI: https://doi.org/10.1007/978-3-319-64206-2_22

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