Triple

T5689147
Position Surface form Disambiguated ID Type / Status
Subject ARIA-H E125385 entity
Predicate temporalRelationToTreatment P53238 FINISHED
Object treatment-emergent during anti-amyloid therapy 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: treatment-emergent during anti-amyloid therapy | Statement: [ARIA-H, temporalRelationToTreatment, treatment-emergent during anti-amyloid therapy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: temporalRelationToTreatment
Context triple: [ARIA-H, temporalRelationToTreatment, treatment-emergent during anti-amyloid therapy]
  • A. temporalRelation
    Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
  • B. treatedAt
    Indicates that a person or patient received medical care or treatment at a particular healthcare facility or location.
  • C. temporalAspect
    Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
  • D. hasTemporalRole
    Indicates that an entity participates in a role or function that is defined, constrained, or characterized by a specific time or temporal context.
  • E. temporality chosen
    Indicates the time-related relationship between events or states, such as their order, duration, or simultaneity.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029014588819094a2a0f6f9b66bab completed March 22, 2026, 5:38 p.m.
PD Predicate disambiguation batch_69c021c0e0408190ab6c3cd3f907e80f completed March 22, 2026, 5:07 p.m.
Created at: March 22, 2026, 3:44 p.m.