Triple

T20758022
Position Surface form Disambiguated ID Type / Status
Subject Chez Panisse E510897 entity
Predicate featuredIn P626 FINISHED
Object Food & Wine NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Food & Wine | Statement: [Chez Panisse, featuredIn, Food & Wine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Food & Wine
Context triple: [Chez Panisse, featuredIn, Food & Wine]
  • A. Food & Wine chosen
    Food & Wine is a long-running American magazine and media brand focused on gourmet cooking, wine, restaurants, and culinary travel.
  • B. Food & Liquor
    Food & Liquor is the critically acclaimed debut studio album by American rapper Lupe Fiasco, known for its socially conscious lyrics and innovative production.
  • C. Food & Wine Festival
    The Food & Wine Festival is a seasonal culinary event at Busch Gardens Williamsburg featuring international cuisine, specialty beverages, and live entertainment.
  • D. Food & Drink
    Food & Drink is a lifestyle and culture section of the Financial Times Weekend edition that focuses on culinary trends, restaurant coverage, recipes, and drinks.
  • E. Gourmet magazine
    Gourmet magazine was a long-running American food and travel publication renowned for its sophisticated recipes, culinary writing, and cultural commentary.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4c909ec8190b05987f1639513f6 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2464fb08190b6b141ca12d9f3f4 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:35 p.m.