skip to main content
10.1145/3078081.3078091acmotherconferencesArticle/Chapter ViewAbstractPublication PagesdatechConference Proceedingsconference-collections
research-article

Dependency Parsing on Late-18th-Century German Aesthetic Writings: A Preliminary Inquiry into Schiller and F. Schlegel

Published:01 June 2017Publication History

ABSTRACT

Data-driven syntactic parsers are usually trained, tested and developed on web-news data. Little has been done to evaluate them on literary genres of different ages, which are still low-resource varieties in terms of syntactic annotation. In this paper, I will describe methodology and results concerning first experiments in testing two different kinds of dependency parsers on aesthetic writings by Schiller and F. Schlegel. First, I trained and tested the parsers on de-ud1.2, a treebank collecting German web-news texts. Second, I manually annotated excerpts by the two authors with syntactic metadata. Third, I tested the parsers on these excerpts, after training them on de-ud1.2

References

  1. Gildea, D. 2001. Corpus variation and parser performance. In Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing (pp. 167--202).Google ScholarGoogle Scholar
  2. Hammond, A., Brooke, J., & Hirst, G. 2013. A tale of two cultures: Bringing literary analysis and computational linguistics together. In Proceedings of the 2nd Workshop on Computational Literature for Literature (CLFL'13), Atlanta, (2013, June).Google ScholarGoogle Scholar
  3. Plank, Barbara, 2011, Domain adaptation for parsing. University Library Groniongen][Host]Google ScholarGoogle Scholar
  4. Freschi, M. 1998, Storia della Civiltà Letteraria Tedesca, Volume Secondo: Ottocento e Novecento, Utet, Milano.Google ScholarGoogle Scholar
  5. Mazza, D. 2013, La Lingua Tedesca: Storia e Testi, Collana Antologie, Carocci Editore, RomaGoogle ScholarGoogle Scholar
  6. Griffero, T. 2012, Storia dell'Estetica Moderna, Edizioni Nuova Cultura, Cross Roads, Annoı, n.1, Roma.Google ScholarGoogle Scholar
  7. Tesnière, L. 1959. Eléments de syntaxe structurale. Librairie C. Klincksieck.Google ScholarGoogle Scholar
  8. Nivre, J. 2005. Dependency grammar and dependency parsing. MSI report, 5133(1959), 1--32.Google ScholarGoogle Scholar
  9. Straka, M., Hajic, J., & Straková, J. 2016. Udpipe: Trainable pipeline for processing conll-u files performing tokenization, morphological analysis, pos tagging and parsing. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia (pp. 4290--4297).Google ScholarGoogle Scholar
  10. Nivre, J., Hall, J., Nilsson, J., Chanev, A., Eryigit, G., Kübler, S., ... & Marsi, E. 2007. MaltParser: A language-independent system for data-driven dependency parsing. Natural Language Engineering, 13(02), 95--135.Google ScholarGoogle ScholarCross RefCross Ref
  11. Bohnet, B. 2010. Very high accuracy and fast dependency parsing is not a contradiction. In: Proceedings of the 23rd International Conference on Computational Linguistics. Association for Computational Linguistics, 2010, p. 89--97.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Buchholz, S., & Marsi, E. 2006. CoNLL-X shared task on multilingual dependency parsing. In Proceedings of the Tenth Conference on Computational Natural Language Learning (2006, June) (pp. 149--164). Association for Computational Linguistics. Google ScholarGoogle ScholarCross RefCross Ref
  13. Joost van Rijsbergen, C. 1975, Information retrieval. Butterworths, London (UK).Google ScholarGoogle Scholar
  14. Nivre, J et al. 2015, Universal Dependencies 1.2.Google ScholarGoogle Scholar
  15. De Marneffe, M. C., Dozat, T., Silveira, N., Haverinen, K., Ginter, F., Nivre, J., & Manning, C. D. 2014. Universal Stanford dependencies: A cross-linguistic typology. In LREC (2014, May) (Vol. 14, pp. 4585--92).Google ScholarGoogle Scholar
  16. Petrov, S., Das, D., & McDonald, R. 2011. A universal part-of-speech tagset. arXiv preprint arXiv:1104.2086.Google ScholarGoogle Scholar
  17. Hajič, J., Ciaramita, M., Johansson, R., Kawahara, D., Martí, M. A., Màrquez, L., ... & Straňák, P. 2009, June. The CoNLL-2009 shared task: Syntactic and semantic dependencies in multiple languages. In Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task (pp. 1--18). Association for Computational Linguistics. Google ScholarGoogle ScholarCross RefCross Ref
  18. Nilsson, J., & Nivre, J. 2008. MaltEval: an Evaluation and Visualization Tool for Dependency Parsing. In LREC. (2008, May).Google ScholarGoogle Scholar
  19. Ballesteros, M., Nivre, J. 2012. MaltOptimizer: A System for MaltParser Optimization. In: LREC. 2012. p. 2757--2Google ScholarGoogle Scholar
  20. Björkelund, A., Bohnet, B., Hafdell, L., and Nugues, P. 2010. A high-performance syntactic and semantic dependency parser. In Coling 2010: Demonstration Volume, pages 33--36, Beijing, August 23-27 2010.Google ScholarGoogle Scholar

Index Terms

  1. Dependency Parsing on Late-18th-Century German Aesthetic Writings: A Preliminary Inquiry into Schiller and F. Schlegel

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      DATeCH2017: Proceedings of the 2nd International Conference on Digital Access to Textual Cultural Heritage
      June 2017
      179 pages
      ISBN:9781450352659
      DOI:10.1145/3078081

      Copyright © 2017 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 1 June 2017

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

      Acceptance Rates

      DATeCH2017 Paper Acceptance Rate29of37submissions,78%Overall Acceptance Rate60of86submissions,70%
    • Article Metrics

      • Downloads (Last 12 months)1
      • Downloads (Last 6 weeks)0

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader