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---
license: unknown
dataset_info:
- config_name: corpus
features:
- name: query_id
dtype: string
- name: snippets
dtype: string
- name: air_date
dtype: string
- name: category
dtype: string
- name: value
dtype: string
- name: round
dtype: string
- name: show_number
dtype: int32
- name: doc_id
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 6252715344
num_examples: 14120776
download_size: 3271155810
dataset_size: 6252715344
- config_name: qa_data
features:
- name: query_id
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: search_results
struct:
- name: related_links
sequence: string
- name: snippets
sequence: string
- name: titles
sequence: string
- name: urls
sequence: string
- name: doc_id
sequence: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 6503932619
num_examples: 173397
- name: test
num_bytes: 1830028629
num_examples: 43350
download_size: 5008413626
dataset_size: 8333961248
configs:
- config_name: corpus
data_files:
- split: train
path: corpus/train-*
- config_name: qa_data
data_files:
- split: train
path: qa_data/train-*
- split: test
path: qa_data/test-*
---
# preprocessed_SearchQA
The SearchQA question-answer pairs originate from J! Archive2, which comprehensively archives all question-answer pairs
from the renowned television show Jeopardy! The passages, sourced from Google search web page snippets.
We offer passage metadata, encompassing details like 'air_date,' 'category,' 'value,' 'round,' and 'show_number,'
enabling you to enhance retrieval performance at your discretion.
Should you require further details about SearchQA, please refer to below links.
[Github](https://github.com/nyu-dl/dl4ir-searchQA)<br>
[Paper](https://arxiv.org/abs/1704.05179)<br>
The dataset is derived from [searhQA](https://huggingface.co/datasets/search_qa).<br>
This preprocessed dataset is for RAG. For more information about our task, visit our [repository](https://github.com/NomaDamas/RAGchain)!<br>
Preprocess SearchQA dataset code for RAG benchmark. <br>
More information, refer to this link! [huggingface](https://huggingface.co/datasets/NomaDamas/search_qa_split)
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