Triple

T9356701
Position Surface form Disambiguated ID Type / Status
Subject Setting Free the Bears E225156 entity
Predicate hasPlaceInFiction P88124 FINISHED
Object Vienna Zoo animal-liberation plot 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: Vienna Zoo animal-liberation plot | Statement: [Setting Free the Bears, hasPlaceInFiction, Vienna Zoo animal-liberation plot]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPlaceInFiction
Context triple: [Setting Free the Bears, hasPlaceInFiction, Vienna Zoo animal-liberation plot]
  • A. hasGroundsInFiction
    Indicates that something is based on, justified by, or finds its origin within fictional works or narratives.
  • B. hasRelativeInFiction
    Indicates that one entity has a relative or family member who appears as a character within a fictional work associated with the other entity.
  • C. hasPlaceInCanon
    Indicates that something holds a specific status or position within an established canon or authoritative body of works.
  • D. hasChildInFiction
    Indicates that a fictional work or character includes another character as their child within the fictional narrative.
  • E. hasFictionalWork
    Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
  • F. None of above. chosen

Provenance (4 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4fee9d4c8190a7d121c9487ccca2 completed April 1, 2026, 5:03 p.m.
PD Predicate disambiguation batch_69cc7a68ab9481909f97cb70764697cc completed April 1, 2026, 1:52 a.m.
PDg Predicate description generation batch_69cc955a38108190b602d1e73725f11b completed April 1, 2026, 3:47 a.m.
Created at: March 30, 2026, 7:42 p.m.