Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
License:
File size: 1,952 Bytes
1fe18c7 4ea5242 1fe18c7 4ea5242 023e7a8 1fe18c7 4ea5242 023e7a8 5d958fb 1fe18c7 5d958fb |
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---
dataset_info:
- config_name: corpus
features:
- name: _id
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: corpus
num_bytes: 11814444.868325485
num_examples: 22933
download_size: 6046630
dataset_size: 11814444.868325485
- config_name: default
features:
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dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: float64
splits:
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num_bytes: 1110.7605332063795
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features:
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dtype: string
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dtype: string
splits:
- name: queries
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num_examples: 27
download_size: 2922
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configs:
- config_name: corpus
data_files:
- split: corpus
path: corpus/corpus-*
- config_name: default
data_files:
- split: test
path: data/test-*
- config_name: queries
data_files:
- split: queries
path: queries/queries-*
task_categories:
- question-answering
language:
- en
tags:
- chemistry
- wikipedia
- nq
- natural questions
- chemteb
pretty_name: Chemical Natural Questions
size_categories:
- 10K<n<100K
license: cc-by-nc-sa-4.0
---
# Chemical Natural Questions
This dataset is created from the [mteb/nq](https://huggingface.co/datasets/mteb/nq) dataset on Hugging Face, which is part of the [Natural Questions](https://ai.google.com/research/NaturalQuestions/) dataset containing real user questions issued to Google search, with answers sourced from Wikipedia. In this chemistry-specific subset, we filtered queries related to chemistry by starting from the chemistry category in Wikipedia and traversing up to three levels deep in linked articles. This approach allowed us to focus on chemistry-related queries, providing a targeted subset of the original dataset for domain-specific retrieval tasks. |