Triple

T2506792
Position Surface form Disambiguated ID Type / Status
Subject Food Network E52602 entity
Predicate hasSisterChannel P6991 FINISHED
Object DIY Network E184109 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: DIY Network | Statement: [Food Network, hasSisterChannel, DIY Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DIY Network
Context triple: [Food Network, hasSisterChannel, DIY Network]
  • A. DIY Network chosen
    DIY Network was an American cable television channel focused on do-it-yourself home improvement, renovation, and repair programming.
  • B. HGTV
    HGTV is an American cable television network focused on home improvement, real estate, and interior design programming.
  • C. Better Homes and Gardens
    Better Homes and Gardens is a long-running American lifestyle magazine and brand focused on home décor, gardening, cooking, and family living.
  • D. DIY
    DIY is the commonly used abbreviation for Daerah Istimewa Yogyakarta, a special administrative region and cultural center on the island of Java in Indonesia.
  • E. The Nate Berkus Show
    The Nate Berkus Show was a daytime television talk show hosted by interior designer Nate Berkus, focusing on home makeovers, lifestyle advice, and personal inspiration.
  • 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_69ab4958e76481908a235377dd921c9e completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1cfeb408190ba8107296310dbfc completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1fa7dbb88190815087416b207b54 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:46 p.m.