QASC#

Overview#

QASC (Question Answering via Sentence Composition) is a question-answering dataset with a focus on multi-hop sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science, requiring models to combine multiple facts to arrive at the correct answer.

Task Description#

  • Task Type: Multi-hop Science Question Answering (Multiple-Choice)

  • Input: Science question with 8 answer choices

  • Output: Correct answer letter

  • Focus: Sentence composition and multi-hop reasoning

Key Features#

  • 9,980 grade school science questions

  • 8-way multiple-choice format

  • Requires composing two facts to answer

  • Tests multi-hop reasoning over scientific knowledge

  • Annotated with supporting facts for each question

Evaluation Notes#

  • Default configuration uses 0-shot evaluation

  • Evaluates on validation split

  • Simple accuracy metric

  • Useful for evaluating compositional reasoning

Properties#

Property

Value

Benchmark Name

qasc

Dataset ID

extraordinarylab/qasc

Paper

N/A

Tags

Knowledge, MCQ

Metrics

acc

Default Shots

0-shot

Evaluation Split

validation

Data Statistics#

Metric

Value

Total Samples

926

Prompt Length (Mean)

362.58 chars

Prompt Length (Min/Max)

283 / 505 chars

Sample Example#

Subset: default

{
  "input": [
    {
      "id": "d92a545e",
      "content": "Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B,C,D,E,F,G,H.\n\nClimate is generally described in terms of what?\n\nA) sand\nB) occurs over a wide range\nC) forests\nD) Global warming\nE) rapid changes occur\nF) local weather conditions\nG) measure of motion\nH) city life"
    }
  ],
  "choices": [
    "sand",
    "occurs over a wide range",
    "forests",
    "Global warming",
    "rapid changes occur",
    "local weather conditions",
    "measure of motion",
    "city life"
  ],
  "target": "F",
  "id": 0,
  "group_id": 0,
  "metadata": {}
}

Prompt Template#

Prompt Template:

Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.

{question}

{choices}

Usage#

Using CLI#

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets qasc \
    --limit 10  # Remove this line for formal evaluation

Using Python#

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['qasc'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)