Triple

T32409377
Position Surface form Disambiguated ID Type / Status
Subject Friedrich Heinrich Lewy E828173 entity
Predicate discoveryHasEffectOn P75247 FINISHED
Object understanding of Parkinson's disease pathology 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: understanding of Parkinson's disease pathology | Statement: [Friedrich Heinrich Lewy, discoveryHasEffectOn, understanding of Parkinson's disease pathology]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: discoveryHasEffectOn
Context triple: [Friedrich Heinrich Lewy, discoveryHasEffectOn, understanding of Parkinson's disease pathology]
  • A. hasEffectIn
    Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
  • B. hasDirectEffect
    Indicates that one entity produces an immediate and unmediated impact or change on another entity.
  • C. findsEffect chosen
    Indicates that one entity discovers, identifies, or determines the effect or outcome produced by another entity.
  • D. capturesEffectOf
    Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
  • E. providesEffect
    Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
  • 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_69f34919f300819092b541c6277cd68a completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f7688dd3d08190ad13d0e780570a1c completed May 3, 2026, 3:23 p.m.
PD Predicate disambiguation batch_69f767fcf2f881908bacc7bfc38e68a5 completed May 3, 2026, 3:21 p.m.
Created at: May 1, 2026, 12:53 a.m.