README.md

metadata

dataset_info:
  features:
    - name: sentence_ant_ana
      dtype: string
    - name: antecedent_subtree
      dtype: string
    - name: antecedent_root
      dtype: string
    - name: anaphora
      dtype: string
    - name: category
      dtype: string
    - name: sempos
      dtype: string
    - name: corpus
      dtype: string
    - name: sentence_ant
      dtype: string
    - name: distance
      dtype: int64
    - name: sentence_ana
      dtype: string
    - name: sentence_clear
      dtype: string
  splits:
    - name: train
      num_bytes: 42462814
      num_examples: 44960
    - name: validation
      num_bytes: 5272640
      num_examples: 5620
    - name: test
      num_bytes: 5341909
      num_examples: 5627
  download_size: 34996304
  dataset_size: 53077363
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
size_categories:
  - 10K<n<100K

Dataset Card for pdt_anaphora_czech

This dataset is used for my thesis to fine-tune language models on Czech unstructured text for anaphora resolution.

Dataset Sources

The dataset is based on data from the Prague Dependency Treebank, specifically the PDTC 1.0 (https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-3185)

How to cite

Stano P. and Horák A. Evaluating Prompt-Based and Fine-Tuned Approaches to Czech Anaphora Resolution. International Conference on Text, Speech, and Dialogue, 2025.

@article{stano_horak2025,
   author = "Patrik Stano and Aleš Horák",
   title  = "Evaluating Prompt-Based and Fine-Tuned Approaches to Czech Anaphora Resolution",
   journal= "International Conference on Text, Speech, and Dialogue",
   year   = "2025",
}