Datasets:
metadata
language:
- en
license: cc-by-2.5
task_categories:
- question-answering
- sentence-similarity
dataset_info:
- config_name: question-answer-passages
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: id
dtype: int64
- name: relevant_passage_ids
sequence: int64
splits:
- name: train
num_bytes: 1615888.0491629583
num_examples: 4012
- name: test
num_bytes: 284753.9508370418
num_examples: 707
download_size: 1309572
dataset_size: 1900642
- config_name: text-corpus
features:
- name: passage
dtype: string
- name: id
dtype: int64
splits:
- name: test
num_bytes: 60166919
num_examples: 40181
download_size: 35304894
dataset_size: 60166919
configs:
- config_name: question-answer-passages
data_files:
- split: train
path: question-answer-passages/train-*
- split: test
path: question-answer-passages/test-*
- config_name: text-corpus
data_files:
- split: test
path: text-corpus/test-*
tags:
- biology
- medical
- rag
This dataset is a subset of a training dataset by the BioASQ Challenge, which is available here.
It is derived from rag-datasets/rag-mini-bioasq
.
Modifications include:
- filling in missing passages (some of them contained
"nan"
instead of actual text), - changing
relevant_passage_ids
' type from string to sequence of ints, - deduplicating the passages (removed 40 duplicates) and fixing the
relevant_passage_ids
in QAP triplets to point to the corrected, deduplicated passages' ids, - splitting QAP triplets into train and test splits.