document_id string | document_text string | document_filename string | document_metadata dict | document_summary string | summarization_model string | chunks list | multihop_chunks list |
|---|---|---|---|---|---|---|---|
b7a2fa52-f136-44da-bf66-02196abe4c4b | "5\n2\n0\n2\n\nr\np\nA\n2\n\n]\nL\nC\n.\ns\nc\n[\n\n1\nv\n3\n3\n8\n1\n0\n.\n4\n0\n5\n2\n:\nv\ni\nX\n(...TRUNCATED) | yourbench_arxiv_paper.md | {
"file_size": 133539
} | "YourBench is an open-source, automated framework that generates dynamic, domain-specific, and relia(...TRUNCATED) | Qwen/Qwen3-4B-Instruct-2507 | [{"chunk_id":"b7a2fa52-f136-44da-bf66-02196abe4c4b_0","chunk_text":"5\n2\n0\n2\n\nr\np\nA\n2\n\n]\nL(...TRUNCATED) | [{"chunk_ids":["b7a2fa52-f136-44da-bf66-02196abe4c4b_63","b7a2fa52-f136-44da-bf66-02196abe4c4b_88"],(...TRUNCATED) |
Test Extensive Custom Schema Demo
This dataset was generated using YourBench (v0.6.0), an open-source framework for generating domain-specific benchmarks from document collections.
Pipeline Steps
- ingestion: Read raw source documents, convert them to normalized markdown and save for downstream steps
- chunking: Split texts into token-based single-hop and multi-hop chunks
- single_shot_question_generation: Generate standalone question-answer pairs per chunk using LLM
Reproducibility
To reproduce this dataset, use YourBench v0.6.0 with the following configuration:
hf_configuration:
hf_dataset_name: test_extensive_custom_schema_demo
hf_organization: $HF_ORGANISATION
push_to_hub: true
model_list:
- model_name: Qwen/Qwen3-4B-Instruct-2507
base_url: http://us-east-1.sumuk.org:9100/stargate.neon-pentatonic.ts.net/30000/v1/
api_key: $API_KEY
max_concurrent_requests: 8
pipeline:
ingestion:
source_documents_dir: test_extensive_schema
output_dir: data/processed
supported_file_extensions:
- .md
- .txt
- .pdf
chunking:
l_max_tokens: 300
token_overlap: 100
single_shot_question_generation:
single_shot_system_prompt: custom_single_shot_system_prompt.md
single_shot_user_prompt: custom_single_shot_user_prompt.md
chunk_sampling:
enable: false
num_samples: 100
strategy: random
random_seed: 42
use_structured_outputs: false
structured_fallback: true
custom_schema_path: test_extensive_schema/schema.py
custom_schema_class: ExtensiveQuestion
custom_schema_auto_batch: true
(This dataset card was automatically generated by YourBench)
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