Datasets:

sentence-transformers
/

askubuntu

dataset_info:
  features:
    - name: query
      dtype: string
    - name: positive
      list: string
    - name: negative
      list: string
  splits:
    - name: train
      num_bytes: 74263739
      num_examples: 12724
    - name: dev
      num_bytes: 238604
      num_examples: 200
    - name: test
      num_bytes: 239279
      num_examples: 200
  download_size: 42752991
  dataset_size: 74741622
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: dev
        path: data/dev-*
      - split: test
        path: data/test-*
language:
  - en
tags:
  - sentence-transformers
pretty_name: 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 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:

{
  "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