Luxury Hotel Dining Catalog Attribute Extraction Dataset
- Records
- 5000
- Size
- 0.3GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
This dataset contains natural-language descriptions of luxury hotel restaurants, bars, and dining experiences, organized into structured attributes such as venue name, venue type, service periods, service formats, cuisines, and dietary restrictions or accommodations. Its catalog coverage includes information such as breakfast, lunch, dinner, and all-day service, as well as dine-in, room service, buffet, and afternoon tea; the actual records depend on the dataset contents. It is suitable for structured-output supervised fine-tuning, dining catalog organization, hotel product information retrieval, and attribute extraction evaluation.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| cuisines | array | Cuisines or primary culinary styles mentioned in the description. |
| venue_name | string | Name of the restaurant, bar, or dining experience extracted from the source description. |
| venue_type | string | Primary category of the dining catalog entry, such as a restaurant, bar, or dining experience. |
| service_formats | array | Dining service formats, such as dine-in, room service, buffet, or afternoon tea. |
| service_periods | array | Periods when the venue or experience provides service, such as breakfast, lunch, dinner, or all-day service. |
| source_description | string | Natural-language description of a dining venue or experience, provided as the input for attribute extraction. |
| dietary_restrictions | array | Dietary restrictions or accommodations mentioned in the description, such as vegetarian, vegan, gluten-free, or halal options. |
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 dining information does the dataset contain?
- Natural-language descriptions of luxury hotel restaurants, bars, and dining experiences are paired with attributes such as venue name, venue type, service periods, service formats, cuisines, and dietary restrictions or accommodations. The actual records and field contents depend on the dataset files.
- Which model tasks is the dataset suitable for?
- It can support structured-output supervised fine-tuning to extract catalog attributes from dining descriptions. It can also be used to organize hotel dining catalogs, improve information retrieval, and evaluate attribute extraction performance.
- How can I check the data format and quality?
- The schema separates source descriptions from their corresponding attributes, making it easier to construct model inputs and structured targets. Before use, review the samples, field definitions, missing-value patterns, and delivery format, then validate them against your project requirements.
- How can I obtain the data, and what are the licensing terms?
- Check the dataset product page or the provider's designated channel for samples, delivery specifications, and access options. Licensing scope, commercial-use permissions, and redistribution restrictions are governed by the terms for this specific dataset product.
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Cite this Work
@dataset{Mobiusi2026,
title={Luxury Hotel Dining Catalog Attribute Extraction Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/ef5bf55d627576acef396d7d898fb5f9?dataset_scene_cate_type=4},
urldate={2026-10-10},
keywords={luxury hotel dining data, hotel restaurant catalog, dining attribute extraction, hotel dining dataset, cuisine identification, dietary restriction detection, structured output SFT, dining catalog data},
version={1.0}
}Using this in research? Please cite us.