Home Media Device Model and Variant Attribute Extraction Dataset
- Records
- 3120
- Size
- 0.2GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
This dataset focuses on catalog entries for home media servers and players, with product titles, descriptions, and specifications that mention specific models, product series, and configuration variants. Its examples emphasize separating model-level attributes from series-level information and preserving an unavailable status when the catalog does not provide clear evidence, helping reduce attribute misattribution. It supports structured-output fine-tuning, catalog attribute extraction, and model information validation.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| product_series | string | The product family or series named in the listing, kept separate from the specific model or variant. Use an empty string if not stated. |
| device_category | string | The most specific home media device category supported by the listing. |
| attribute_results | array | Per-attribute extraction results. Include relevant attributes even when the catalog does not provide them, using the not_provided status in that case. Do not treat series-level information as model-specific unless the listing makes that association explicit. |
| catalog_entry_text | string | The original product title, description, and specifications as provided in the catalog. Preserve the source wording for downstream extraction. |
| model_match_status | string | Indicates whether the listing provides enough evidence to associate the extracted attributes with a specific model or variant. |
| variant_configuration | string | The configuration that distinguishes this listing from related models or variants, such as storage size, included tuner, or regional version. Use an empty string if not stated. |
| identified_model_number | string | The exact model number explicitly associated with the listed item. Use an empty string if the listing does not identify it clearly. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- Examples are based on catalog entries for home media servers and players. They include product title, description, and specification text, along with extracted information such as model number, product series, variant configuration, device category, and attribute results.
- How does the dataset handle model and series information?
- It keeps specific models separate from product series. An attribute is assigned to the listed model or variant only when the catalog explicitly supports that association; attributes not clearly stated are marked as not provided.
- Which training or evaluation tasks does it support?
- It supports structured-output fine-tuning, product catalog attribute extraction, model and variant matching, and training or evaluation for detecting information missing from catalog listings.
- How can I access the dataset, and what are the licensing terms?
- Check the dataset product page or accompanying license documentation for access options, permitted use, and commercial terms. Confirm the applicable terms and data provenance before use.
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Cite this Work
@dataset{Mobiusi2026,
title={Home Media Device Model and Variant Attribute Extraction Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/a3e90a132fc8b4f05339c8e079117824?dataset_scene_id=6},
urldate={2026-10-26},
keywords={home media device dataset,media server model,media player attribute extraction,product variant identification,product catalog data,model attribute matching,structured output SFT,e-commerce attribute extraction},
version={1.0}
}Using this in research? Please cite us.