Version 1 (modified by Ales Horak, 22 months ago) (diff)

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Parsing of Czech: Between Rules and Stats

IA161 NLP in Practice Course, Course Guarantee: Aleš Horák

Prepared by: Miloš Jakubíček

State of the Art


  1. Zhang, Y., Zhou, H., & Li, Z. (2020). Fast and Accurate Neural CRF Constituency Parsing. arXiv preprint arXiv:2008.03736.
  2. Qi, P., Dozat, T., Zhang, Y., & Manning, C. D. (2019). Universal dependency parsing from scratch. arXiv preprint arXiv:1901.10457.
  3. Straka, M., Straková, J., & Hajič, J. (2019). Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER. In International Conference on Text, Speech, and Dialogue (pp. 137-150). Springer, Cham.
  4. Baisa, V. and Kovář, V. (2014). Information extraction for Czech based on syntactic analysis. In Vetulani, Z. and Mariani, J., editors,Human Language Technology Challenges for Computer Science and Linguistics, pages 155–165. Springer International Publishing.

Practical Session

We will develop/adjust the grammar of the SET parser.

  1. Download the SET parser with evaluation dataset
  2. Unzip the downloaded file
  3. Go to the unziped folder
    cd ukol_ia161-parsing
  4. Test the prepared program that analyses 100 selected sentences
    make set_trees
    make compare
    The output should be
    ./ data/trees/pdt2_etest data/trees/set_pdt2_etest-sel100
    UAS =  66.1 %
    You can see detailed evaluation (sentence by sentence) with
    make compare SENTENCES=1
    You can watch differences for one tree with
    make diff SENTENCE=00009
    Exit the diff by pressing q.
    You can watch the two trees with (python-qt4 must be installed in the system)
    make view SENTENCE=00009
    For remote tree view, you may run
    make html SENTENCE=00009
    And point your browser to the html/index.html file.
    You can extract the text of the sentence easily with
    make text SENTENCE=00009
    English translation of the Czech sentences can be obtained via
    make texttrans SENTENCE=00009
  5. Look at the files:
    • data/vert/pdt2_etest-sel100 - 100 input sentences in vertical format. The tag format is the Prague Dependency Treebank positional tagset
    • data/trees/pdt2_etest - 100 gold standard dependency trees from the Prague Dependency Treebank
    • data/trees/set_pdt2_etest-sel100 - 100 trees output from SET by running make set_trees
    • grammar.set - the grammar used in running SET


  1. Study the SET documentation. The tags used in the grammar are in the Brno tagset.
  2. Develop better grammar - repeat the process:
    edit grammar.set # use your favourite editor
    make set_trees
    make compare
    to improve the original UAS
  3. Write the final UAS in grammar.set
    # This is the SET grammar for Czech used in IA161 course
    # ===========   resulting UAS =  66.1 %  ===================
  4. Upload your grammar.set to the homework vault.

Attachments (2)

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