Datasets:
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---
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](https://github.com/taolei87/askubuntu).
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](https://huggingface.co/datasets/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 |