Triple

T18145156
Position Surface form Disambiguated ID Type / Status
Subject 30 Minute Meals E434368 entity
Predicate mediaFranchiseOf P7740 FINISHED
Object Rachael Ray media properties LITERAL 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: Rachael Ray media properties | Statement: [30 Minute Meals, mediaFranchiseOf, Rachael Ray media properties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mediaFranchiseOf
Context triple: [30 Minute Meals, mediaFranchiseOf, Rachael Ray media properties]
  • A. mediaFranchiseType
    Indicates the specific kind or category of media franchise that an entity belongs to (e.g., film series, TV franchise, game franchise).
  • B. hasMediaFranchise chosen
    Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
  • C. fandomScope
    Indicates the extent or boundaries of a fandom-related relationship, such as how broadly or narrowly a fan’s interest, participation, or recognition applies.
  • D. fandomType
    Indicates the specific category or kind of fandom relationship that exists between an entity and the subject of that fandom.
  • E. fandomFocus
    Indicates that one entity is primarily centered on, dedicated to, or concerned with the fan community or fan-related aspects of another entity.
  • F. None of above.

Provenance (3 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de32d3f88190bd9f406729716407 completed April 19, 2026, 1:52 p.m.
PD Predicate disambiguation batch_69e43317d11c81908d1dc14921566b47 completed April 19, 2026, 1:42 a.m.
Created at: April 10, 2026, 10:29 a.m.