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sentence-transformers/askubuntu

Dataset Card for AskUbuntu The AskUbuntu dataset (Lei et al., 2016) is a collection of preprocessed questions taken from AskUbuntu.com 2014 corpus dump. It also comes with 400*20 mannual annotations, marking pairs of questions as "similar" or "non-similar". The dataset is sourced from the original GitHub repository. Note that for the train split, the "positive" is the list of similar questions according to AskUbuntu, and "negative" is a list of randomly selected questions. For… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/askubuntu.

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Dataset Card

Dataset Card for AskUbuntu

The AskUbuntu dataset (Lei et al., 2016) is a collection of preprocessed questions taken from AskUbuntu.com 2014 corpus dump. It also comes with 400*20 mannual annotations, marking pairs of questions as "similar" or "non-similar". The dataset is sourced from the original GitHub repository.

Note that for the train split, the "positive" is the list of similar questions according to AskUbuntu, and "negative" is a list of randomly selected questions. For dev and test, the "positive" are human-annotated and may be empty. Unlike the original dataset, the "positive" data is not a subset of the "negative" data, they're mutually exclusive.

See also sentence-transformers/askubuntu-questions for all AskUbuntu questions in this dataset.

Dataset Details

  • —Columns: "query", "positive", "negative"
  • —Column types: str, list[str], list[str]
  • —Examples:
python
    {
      "query": "system running in low graphic mode ( ubuntu without monitor )",
      "positive": [
        "getting system to boot in headless mode set-up without display problems"
      ],
      "negative": [
        "software center not progress showing mergelist error",
        "how to install google earth or draftsight for 64-bit os ?",
        "how to install a huawei ec-226 usb modem ?",
        ...
      ]
    }
  • —Collection strategy: Downloading the train_random.txt, dev.text, and test.txt files from the original source, and mapping the query IDs to the query texts.
  • —Deduplicated: No