Triple

T27701721
Position Surface form Disambiguated ID Type / Status
Subject Let’s Explore Diabetes with Owls E698443 entity
Predicate containsFictionalizedElements P93730 FINISHED
Object true 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: true | Statement: [Let’s Explore Diabetes with Owls, containsFictionalizedElements, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: containsFictionalizedElements
Context triple: [Let’s Explore Diabetes with Owls, containsFictionalizedElements, true]
  • A. hasFictionalContent chosen
    Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
  • B. hasFictionalFrame
    Indicates that one entity is presented or interpreted within the context of a fictional narrative, scenario, or imaginative framework provided by another entity.
  • C. hasFictionalScope
    Indicates that something pertains to, applies within, or is limited to a fictional or imagined context rather than real-world scope.
  • D. portraysFictionalized
    Indicates that one entity represents or depicts another entity in a fictionalized or altered manner, rather than as a strictly accurate portrayal.
  • E. hasFictionalType
    Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
  • 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_69ef590ea74081908f0cd7500d85fa27 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69fd389cb28c819099a77e28d25f258a completed May 8, 2026, 1:13 a.m.
PD Predicate disambiguation batch_69fd3826d8048190ada79a5868d1d7f3 completed May 8, 2026, 1:11 a.m.
Created at: April 27, 2026, 2:57 p.m.