Datasets:

stefanbschneider
/

lfqa_preprocessed

dataset_info:
  features:
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: context
      sequence: string
  splits:
    - name: train
      num_bytes: 1103867201.974574
      num_examples: 218894
    - name: validation
      num_bytes: 14929675.549668875
      num_examples: 2904
  download_size: 651254676
  dataset_size: 1118796877.5242429
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
license: mit
task_categories:
  - question-answering
  - text2text-generation
language:
  - en
size_categories:
  - 100K<n<1M

Dataset Card for "stefanbschneider/lfqa_preprocessed"

Table of Contents
Dataset Description
- Dataset Summary
Dataset Structure
Additional Information
- Licensing Information

Dataset Description

The dataset contains simple, long-form answers to questions and corresponding contexts. Similar to ELI5 but with context.

This dataset is a filtered version of LLukas22/lfqa_preprocessed, which in turn is a processed and simplified version of of vblagoje's lfqa_support_docs and lfqa datasets.

This dataset (stefanbschneider/lfqa_preprocessed) has filtered out overly long answers (around 3%). It can be reproduced with the notebook process-lfqa-dataset.ipynb.

LLukas22/lfqa_preprocessed	stefanbschneider/lfqa_preprocessed

Max answer length: 26123 chars	Max answer length: 7035 chars (more than 3x shorter)
Num answers (train): 226147	Num answers (train): 218894 (~3% less)

Details of the original LFQA dataset: https://towardsdatascience.com/long-form-qa-beyond-eli5-an-updated-dataset-and-approach-319cb841aabb

Dataset Structure

Data Instances

An example of 'train' looks as follows.

{
    "question": "what's the difference between a forest and a wood?",
    "answer": "They're used interchangeably a lot. You'll get different answers from different resources, but the ...",
    "context": [
        "Wood is divided, according to its botanical origin, into two kinds: softwoods, ...",
        "Processing and products differs especially with regard to the distinction between softwood and hardwood ..."
    ]
}

Data Fields

The data fields are the same among all splits.

question: a string feature.
answer: a string feature.
context: a list feature containing string features.

Data Splits

name	train	validation
	218894	2904

Additional Information

Licensing Information

This dataset is distributed under the MIT licence.