Data · dataset · 2022
SearchQA
Listed in Hugging Face Datasets
We publicly release a new large-scale dataset, called SearchQA, for machine comprehension, or question-answering.
Description
Unlike recently released datasets, such as DeepMind CNN/DailyMail and SQuAD, the proposed SearchQA was constructed to reflect a full pipeline of general question-answering. That is, we start not from an existing article and generate a question-answer pair, but start from an existing question-answer pair, crawled from J!
Archive, and augment it with text snippets retrieved by Google. Following this approach, we built SearchQA, which consists of more than 140k question-answer pairs with each pair having 49.6 snippets on average. Each question-answer-context tuple of the SearchQA comes with additional meta-data such as the snippet's URL, which we believe will be valuable resources for future research.
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We conduct human evaluation as well as test two baseline methods, one simple word selection and the other deep learning based, on the SearchQA. We show that there is a meaningful gap between the human and machine performances. This suggests that the proposed dataset could well serve as a benchmark for question-answering.
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/kyunghyuncho/search_qa ↗
landing page · from Hugging Face
Documentation and papers
- arXiv:1704.05179 arxiv.org/abs/1704.05179 ↗
publication · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/kyunghyuncho/search_qa ↗
metadata API · from Hugging Face
Topics
- Stated by source
- question answering
- From keywords
- Computer Science & AI
- Inferred from text
- Text 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | kyunghyuncho/search_qa | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · Hugging Face | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[task].hf_task:question-answering | source · Hugging Face | connector:huggingface@1.0.0 | /tags[task_categories:*] |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| license_text | source · Hugging Face | connector:huggingface@1.0.0 | |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |