Triple

T27740370
Position Surface form Disambiguated ID Type / Status
Subject India's Next Top Model E701835 entity
Predicate formatAdaptationOf P43664 FINISHED
Object America's Next Top Model NE NERFINISHED

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: America's Next Top Model | Statement: [India's Next Top Model, formatAdaptationOf, America's Next Top Model]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: formatAdaptationOf
Context triple: [India's Next Top Model, formatAdaptationOf, America's Next Top Model]
  • A. isAdaptation chosen
    Indicates that one work is derived from, based on, or reinterprets the content of another work.
  • B. formatMayChange
    Indicates that the format or structure of something is subject to modification and may not remain consistent over time.
  • C. mediaAdaptationSettingOf
    Indicates that a media adaptation (such as a film, series, or game) is set in the narrative world or environment of a particular original work.
  • D. formatVariantOf
    Indicates that one entity is an alternative representation or version of another entity that differs only in format while preserving the same underlying content or meaning.
  • E. screenAdaptationFrom
    Indicates that a screen-based work (such as a film or TV show) is an adaptation derived from another source work.
  • 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_69ef6a53c7388190899baa6daf42301c completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6640168948190811bd5f933a87cf5 completed May 2, 2026, 8:52 p.m.
PD Predicate disambiguation batch_69f6633451948190bcc0410602bb4914 completed May 2, 2026, 8:48 p.m.
Created at: April 27, 2026, 4:10 p.m.