Triple

T32205400
Position Surface form Disambiguated ID Type / Status
Subject Eat This, Not That When You’re Expecting E822653 entity
Predicate basedOn P98 FINISHED
Object Eat This, Not That franchise
The Eat This, Not That franchise is a popular health and nutrition brand that compares common food choices to guide people toward lower-calorie, more nutritious options through books, articles, and other media.
 E1997051 NE FINISHED

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: Eat This, Not That franchise | Statement: [Eat This, Not That When You’re Expecting, basedOn, Eat This, Not That franchise]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eat This, Not That franchise
Triple: [Eat This, Not That When You’re Expecting, basedOn, Eat This, Not That franchise]
Generated description
The Eat This, Not That franchise is a popular health and nutrition brand that compares common food choices to guide people toward lower-calorie, more nutritious options through books, articles, and other media.

Provenance (5 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_69f349093174819086e633c190a51aa8 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb840e288190b6b188b7f6928601 completed May 3, 2026, 3:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f3b934c108190ae4118be13ac79f9 completed June 14, 2026, 11:38 p.m.
NEDg Description generation batch_6a2f3c207d988190835c5bda034bbc6c completed June 14, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_6a2f3ef33fc08190bdedc81c93429535 completed June 14, 2026, 11:53 p.m.
Created at: May 1, 2026, 12:36 a.m.