Dataset:

Task Categories: structure-prediction
Languages: da
Multilinguality: monolingual
Size Categories: 1K<n<10K
Licenses: cc-by-sa-4.0
Language Creators: found
Annotations Creators: expert-generated

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Dataset Summary

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Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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Data Fields

Data Fields:

  • q_id: a string question identifier for each example, corresponding to its ID in the Pushshift.io Reddit submission dumps.
  • subreddit: One of explainlikeimfive, askscience, or AskHistorians, indicating which subreddit the question came from
  • title: title of the question, with URLs extracted and replaced by URL_n tokens
  • title_urls: list of the extracted URLs, the nth element of the list was replaced by URL_n
  • sent_id: a string identifier for each example
  • text: a string, the original sentence (not tokenized)
  • tok_ids: a list of ids (int), one for each token
  • tokens: a list of strings, the tokens
  • lemmas: a list of strings, the lemmas of the tokens
  • pos_tags: a list of strings, the part-of-speech tags of the tokens
  • morph_tags: a list of strings, the morphological tags of the tokens
  • dep_ids: a list of ids (int), the id of the head of the incoming dependency for each token
  • dep_labels: a list of strings, the dependency labels
  • ner_tags: a list of strings, the named entity tags (BIO format)

Data Splits

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

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Contributions

Thanks to @ophelielacroix, @lhoestq for adding this dataset.

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