Triple

T7772151
Position Surface form Disambiguated ID Type / Status
Subject Valerie Bertinelli E179097 entity
Predicate employer P7 FINISHED
Object Food Network E52602 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: Food Network | Statement: [Valerie Bertinelli, employer, Food Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Food Network
Context triple: [Valerie Bertinelli, employer, Food Network]
  • A. Food Network chosen
    Food Network is a cable television channel dedicated to food, cooking, and culinary lifestyle programming.
  • B. Cooking Channel
    Cooking Channel is an American cable television network focused on instructional cooking shows, culinary exploration, and food-related entertainment.
  • C. Food Network Magazine
    Food Network Magazine is a lifestyle and cooking publication that features recipes, chef profiles, and food-related entertainment inspired by the Food Network television channel.
  • D. Recipe.TV
    Recipe.TV is a lifestyle television network and streaming channel focused on cooking, culinary travel, and food-related programming.
  • E. Bravo (TV network)
    Bravo is an American cable television network best known for its reality programming and pop-culture-focused series such as the Real Housewives franchise and Top Chef.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c7046048688190a6cbc64e82b58eca completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7ee407881908e591d216c504b24 completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:11 p.m.