46 lines
1.7 KiB
Python

"""TriviaQA (official source: mandarjoshi/trivia_qa, rc.wikipedia config).
rc.wikipedia = reading-comprehension WITH the Wikipedia evidence document
(open-book, aligned with evalscope's default); rc.nocontext is the
closed-book variant (pass --subset rc.nocontext).
"""
from ..sample import Sample
from ..registry import register_dataset
from ..spec import DatasetSpec
@register_dataset(
DatasetSpec(
name='trivia_qa',
source='mandarjoshi/trivia_qa', # official: https://huggingface.co/datasets/mandarjoshi/trivia_qa
subset='rc.wikipedia', # open-book (evalscope parity); --subset rc.nocontext for closed
split='validation',
task_type='qa',
tags=['knowledge', 'openqa'],
description='TriviaQA with Wikipedia evidence (open-book); any alias counts.',
)
)
def trivia_qa():
def to_sample(record: dict) -> Sample:
answer = record['answer'] # {'value': ..., 'aliases': [...], ...}
targets = [answer['value']] + list(answer.get('aliases') or [])
# open-book: the Wikipedia evidence document (runner prepends it via
# metadata['context'] when assembling the prompt)
wiki = ''
entity = record.get('entity_pages') or {}
for doc in (entity.get('wiki_content') or [])[:1]:
wiki = doc or ''
break
search = record.get('search_results') or {}
if not wiki:
wiki = '\n'.join((search.get('search_context') or [])[:2])
return Sample(
input=record['question'],
target=targets, # multi-target: any alias counts
metadata={'question_id': record.get('question_id'),
'context': wiki or None},
)
return to_sample