Triple

T34168387
Position Surface form Disambiguated ID Type / Status
Subject Buenos Aires Zoo E876476 entity
Predicate transformationGoal P143170 FINISHED
Object reduce captivity of animals 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: reduce captivity of animals | Statement: [Buenos Aires Zoo, transformationGoal, reduce captivity of animals]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: transformationGoal
Context triple: [Buenos Aires Zoo, transformationGoal, reduce captivity of animals]
  • A. goalOfRealization chosen
    Indicates the intended outcome or objective that an action, process, or plan is meant to bring into reality or achieve.
  • B. settingOfTransformation
    Indicates the place, context, or environment in which a transformation of an entity or state occurs.
  • C. transportGoal
    Indicates that an entity has the objective or intended outcome of moving or conveying something or someone from one place to another.
  • D. showsTransformationOf
    Indicates that one entity visually or conceptually presents the process or result of another entity changing from one state, form, or condition to another.
  • E. restorationGoal
    Indicates that an action or plan is intended to return something to a previous, original, or improved state or condition.
  • 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_69f349ad97ac8190bf1f17417c970e64 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69ff1a972bf08190860696ffcd887c0f completed May 9, 2026, 11:29 a.m.
PD Predicate disambiguation batch_69ff184005d88190bf38283ebc499b28 completed May 9, 2026, 11:19 a.m.
Created at: May 1, 2026, 1:54 a.m.