README.md

metadata

language:
  - en
pretty_name: QASPER Chat-Format
license: unknown
task_categories:
  - question-answering
task_ids:
  - extractive-qa
source_datasets:
  - allenai/qasper
tags:
  - text
  - science
  - chat-format
  - instruction-tuning
  - datasets
  - allenai/qasper
  - evidence-selection
  - arxiv:2105.03011

QASPER (Chat-Format Preparation)

This dataset is a chat-format preparation of QASPER for supervised fine-tuning (SFT).

Format

This format is commonly referred to as:

• chat-format SFT data
• instruction-tuning conversations
• OpenAI-style messages format

Included files

• train.jsonl
• validation.jsonl
• stats.json
• prepare_qasper_unsloth.py

Source

• Base dataset: allenai/qasper

Original Dataset Highlights

• Original dataset: allenai/qasper
• Focus: question answering on scientific NLP papers with evidence selection.
• Reported scale on source card: 5,049 questions over 1,585 papers.
• Key annotation properties: multiple answer types (free-form, extractive, yes/no, unanswerable) and evidence annotations.
• Paper: A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers

Preparation summary

• One row per (paper, question) using the best available annotation.
• Answer normalization priority:
  1. free-form
  2. yes/no
  3. extractive spans
  4. unanswerable
• Context mode is mixed between:
  • evidence-only
  • full-text
• User prompt follows a question-first structure.

Assistant target is the normalized answer text.

Schema

Each JSONL row contains:

• messages
  • user: text instruction + question + title + abstract + context
  • assistant: text answer
• meta: ids, answer type, context mode, evidence count

Reproduction

python prepare_qasper_unsloth.py