Triple

T28089021
Position Surface form Disambiguated ID Type / Status
Subject federal appellate courts of Argentina E709903 entity
Predicate remedyPower P164031 FINISHED
Object confirm lower court decisions 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: confirm lower court decisions | Statement: [federal appellate courts of Argentina, remedyPower, confirm lower court decisions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: remedyPower
Context triple: [federal appellate courts of Argentina, remedyPower, confirm lower court decisions]
  • A. remedy
    Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
  • B. hasRemedy
    Indicates that one entity serves as a remedy, treatment, or corrective measure for a problem, condition, or undesirable state associated with another entity.
  • C. typeOfRemedy
    Indicates that one entity is a specific kind or category of remedy in relation to another entity.
  • D. powerUp
    Indicates an action where an entity increases or restores another entity’s energy, strength, or functional capacity.
  • E. usesPowerFor
    Indicates that one entity applies or exploits a particular power, energy, or capability for a specific purpose or activity.
  • 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_69ef9b7037f0819095bb90eaccbcaf32 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6416fbf4081909b0913c337927fc4 completed May 2, 2026, 6:24 p.m.
PD Predicate disambiguation batch_69f63c6a8474819091b8c6fe98e3862d completed May 2, 2026, 6:03 p.m.
PDg Predicate description generation batch_69f63fd4f7448190930c723ba7cfce62 completed May 2, 2026, 6:17 p.m.
Created at: April 27, 2026, 8:57 p.m.