Triple

T28114283
Position Surface form Disambiguated ID Type / Status
Subject ClearSight E710576 entity
Predicate clinicalApplication P164050 FINISHED
Object hemodynamic assessment during surgery 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: hemodynamic assessment during surgery | Statement: [ClearSight, clinicalApplication, hemodynamic assessment during surgery]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: clinicalApplication
Context triple: [ClearSight, clinicalApplication, hemodynamic assessment during surgery]
  • A. clinicalApplication chosen
    Indicates that something is used or intended to be used in a practical medical or healthcare setting for diagnosis, treatment, or patient care.
  • B. clinicalSetting
    Indicates that an action, observation, or interaction occurs within a healthcare or medical care environment.
  • C. clinicalEmphasis
    Indicates a focus or priority placed on clinical aspects, practices, or outcomes within a given context or activity.
  • D. clinicalContext
    Indicates the medical situation, setting, or circumstances under which a clinical finding, observation, or action occurs.
  • E. clinicalCondition
    Indicates that one entity has, exhibits, or is associated with a particular medical or health-related condition described by the other 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_69ef9b72f63081909dfbc2c1ddae86c6 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f643ed0b7481908cf25f3afec0a61d completed May 2, 2026, 6:35 p.m.
PD Predicate disambiguation batch_69f641def1e88190a05bf865ced78b23 completed May 2, 2026, 6:26 p.m.
Created at: April 27, 2026, 9:13 p.m.