Triple

T970391
Position Surface form Disambiguated ID Type / Status
Subject Max E20930 entity
Predicate hasContentFrom P22683 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: [Max, hasContentFrom, Food Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Food Network
Context triple: [Max, hasContentFrom, Food Network]
  • A. Food Network chosen
    Food Network is a cable television channel dedicated to food, cooking, and culinary lifestyle programming.
  • B. 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.
  • C. EIT Food
    EIT Food is a European innovation community that brings together businesses, research institutions, and universities to drive innovation and entrepreneurship in the agrifood sector.
  • D. A&E Network
    A&E Network is an American cable and satellite television channel known for its original programming, including documentaries, reality series, and high-quality scripted productions.
  • E. Paramount Network
    Paramount Network is an American cable television channel owned by Paramount Global, known for airing original scripted series, reality shows, and feature films.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b75103688190a14342eef3842984 completed March 1, 2026, 10:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1707339081909c69c7c613eed383 completed March 7, 2026, 12:16 p.m.
Created at: March 1, 2026, 7:40 p.m.