Triple
T28114282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ClearSight |
E710576
|
entity |
| Predicate | clinicalApplication |
P164050
|
FINISHED |
| Object | cardiovascular monitoring |
—
|
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: cardiovascular monitoring | Statement: [ClearSight, clinicalApplication, cardiovascular monitoring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clinicalApplication Context triple: [ClearSight, clinicalApplication, cardiovascular monitoring]
-
A.
clinicalSetting
Indicates that an action, observation, or interaction occurs within a healthcare or medical care environment.
-
B.
clinicalEmphasis
Indicates a focus or priority placed on clinical aspects, practices, or outcomes within a given context or activity.
-
C.
clinicalContext
Indicates the medical situation, setting, or circumstances under which a clinical finding, observation, or action occurs.
-
D.
clinicalCondition
Indicates that one entity has, exhibits, or is associated with a particular medical or health-related condition described by the other entity.
-
E.
clinicalBaseOf
Indicates that one clinical entity serves as the foundational basis or underlying source for another clinical entity (such as a diagnosis, assessment, or decision).
- 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_69ef9b72f63081909dfbc2c1ddae86c6 |
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, 9:13 p.m.