Konferenzbeitrag

Data point selection for genre-aware parsing

In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.

Data point selection for genre-aware parsing

Urheber*in: Rehbein, Ines; Bildhauer, Felix

Namensnennung 4.0 International

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/
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Sprache
Englisch

Thema
Parsing
Korpus <Linguistik>
Textsorte
Sprache

Ereignis
Geistige Schöpfung
(wer)
Rehbein, Ines
Bildhauer, Felix
Ereignis
Veröffentlichung
(wer)
Stroudsburg PA, USA : The Association for Computational Linguistics
(wann)
2018-09-27

URN
urn:nbn:de:bsz:mh39-80007
Letzte Aktualisierung
06.03.2025, 09:00 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
Leibniz-Institut für Deutsche Sprache - Bibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Rehbein, Ines
  • Bildhauer, Felix
  • Stroudsburg PA, USA : The Association for Computational Linguistics

Entstanden

  • 2018-09-27

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