yuyijiong/context_qa_sum_qwen3_synthetic

Context-based QA and Summarization Synthetic Dataset

Overview

This dataset contains synthetic context-based question-answering (QA) and summarization data. The data was synthesized using:

• Source context: openbmb/Ultra-FineWeb
• Synthesis model: Qwen3-30B-A3B-Instruct-2507

Each context is obtained by taking the initial segment of raw pretraining text from Ultra-FineWeb, truncated to at most the corresponding number of tokens, while ensuring the truncation does not occur in the middle of a sentence.

The dataset covers context-based QA and summarization tasks in both English and Chinese. It is organized into single-document and multi-document splits.

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Dataset Structure

Single-Document Tasks

Single-document splits provide one source context per sample, with context lengths close to (and not exceeding) 128, 256, 512, or 1024 tokens. Each sample includes a question, an answer, and summaries derived from that context.

Folder	Language	Context length (tokens)	# Samples
doc_sum_qa_shortsum_synthetic_text_128_en	English	~128	1,879,005
doc_sum_qa_shortsum_synthetic_text_128_zh	Chinese	~128	3,070,655
doc_sum_qa_shortsum_synthetic_text_256_en	English	~256	1,613,809
doc_sum_qa_shortsum_synthetic_text_256_zh	Chinese	~256	2,992,339
doc_sum_qa_shortsum_synthetic_text_512_en	English	~512	1,538,654
doc_sum_qa_shortsum_synthetic_text_512_zh	Chinese	~512	3,446,382
doc_complex_qa_shortsum_synthetic_text_1024_en	English	~1024	1,597,716
doc_complex_qa_shortsum_synthetic_text_1024_zh	Chinese	~1024	2,533,299

Column definitions (single-document):

Column	Description
text_128 / text_256 / text_512 / text_1024	Source context (column name matches the target context length for that split).
question	A regular question grounded in this context.
answer	A brief answer to the question.
summary	A summary of the context.
short_summary	A highly condensed summary of the context.

Note on doc_complex_qa_shortsum_synthetic_text_1024_* splits: These 1024-token splits do not include a summary column. The QA in these splits is complex QA—i.e., questions that require multi-step reasoning and are more challenging than the regular QA in the 128/256/512 splits.

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Multi-Document Tasks

Multi-document splits provide a context formed by multiple documents, each of length approximately 128 tokens. Each sample includes multiple questions over the combined context, with answers and a short summary.

Folder	Language	# Samples
doc_multi_doc_multi_qa_short_sum_synthetic_text_128_en	English	1,861,577
doc_multi_doc_multi_qa_short_sum_synthetic_text_128_zh	Chinese	2,034,612

Column definitions (multi-document):

Column	Description
context	The full context, composed of multiple documents of ~128 tokens each.
questions	Multiple regular questions about this context.
answers	The answer corresponding to each question.
short_summary	A highly condensed summary of the full context.
docs	The original documents used to form the context.
target_docs	For each question, the document(s) that the question is based on.

Intended Use

• This is the training data for Density-aware Soft Context Compression with Semi-Dynamic Compression Ratio . The trained models are here.
• Training / fine-tuning LLMs for (short-)context-based QA and summarization, enhancing its overall ability of context utilization.
• Evaluating LLMs' ability to answer questions or summarize about contextual information.