Triple

T38644864
Position Surface form Disambiguated ID Type / Status
Subject Medic E938688 entity
Predicate RestorationEffect P191315 FINISHED
Object removes negative status effects 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: removes negative status effects | Statement: [Medic, RestorationEffect, removes negative status effects]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: RestorationEffect
Context triple: [Medic, RestorationEffect, removes negative status effects]
  • A. restorationUse
    Indicates the use of something specifically for the purpose of restoring, repairing, or returning another entity to a previous or improved state.
  • B. restorationType
    Indicates the specific kind or category of restoration applied to an entity, such as the method, scope, or approach used to return it to a prior or improved state.
  • C. restorationMeasure
    Indicates that an action or intervention is undertaken to repair, rehabilitate, or return something to a previous or improved state.
  • D. restorationCharacteristics
    Indicates the properties or conditions involved in returning something to a previous or improved state.
  • E. restorationFocus
    Indicates that the primary attention or effort is directed toward repairing, renewing, or returning something to a previous or improved state.
  • 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_69f76ed948ec81908ce7811608a8f359 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdb0de8c08190928cd1323f80ab5c completed May 7, 2026, 6:33 p.m.
PD Predicate disambiguation batch_69fcd9017dd88190b32a73fe78909740 completed May 7, 2026, 6:25 p.m.
PDg Predicate description generation batch_69fcdb0cf6008190b27046b694f84356 completed May 7, 2026, 6:33 p.m.
Created at: May 3, 2026, 4:32 p.m.