task_categories:question-answering language:de language:en license:mit size_categories:1K<n<10K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
dataset_info:
  features:
  - name: id
    dtype: string
  - name: title
    dtype: string
  - name: reference_contexts_en
    sequence: string
  - name: user_input_en
    dtype: string
  - name: reference_en
    dtype: string
  - name: reference_contexts_de
    sequence: string
  - name: user_input_de
    dtype: string
  - name: reference_de
    dtype: string
  splits:
  - name: clean_full_en_de
    num_bytes: 2369380
    num_examples: 1190
  - name: single_qa_en_de
    num_bytes: 465708
    num_examples: 240
  - name: test_half
    num_bytes: 237335
    num_examples: 120
  download_size: 902909
  dataset_size: 3072423
configs:
- config_name: default
  data_files:
  - split: clean_full_en_de
    path: data/clean_full_en_de-*
  - split: single_qa_en_de
    path: data/single_qa_en_de-*
  - split: test_half
    path: data/test_half-*
task_categories:
- question-answering
language:
- de
- en
---

data source: https://github.com/google-deepmind/xquad (base on squad 1.0)

document_en/de.zip contains all 48 documents for answer the question: created by concatenate continous pragraphs

Question,Answer, Context (QAC) pair in english(en) AND german(de)

- clean_full_en_de: 48 documents, 5 paragraphs per document, multiple questions per paragraph
- single_qa_en_de: 48 documents, 5 paragraphs per document, one question per paragraph
- test_half: 24 documents, 5 paragraphs per document, one question per paragraph. All documents are still exist in SQuAD 2.0