Triple
T9855059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persona Knee System |
E239561
|
entity |
| Predicate | clinicalSetting |
P90357
|
FINISHED |
| Object | orthopedic 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: orthopedic surgery | Statement: [Persona Knee System, clinicalSetting, orthopedic surgery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clinicalSetting Context triple: [Persona Knee System, clinicalSetting, orthopedic surgery]
-
A.
clinicalRole
Indicates the specific function, responsibility, or position an entity holds within a clinical or healthcare context.
-
B.
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).
-
C.
clinicalForm
Indicates the specific clinical manifestation or presentation type associated with a medical condition or case.
-
D.
medicalEvent
Indicates that a specific health-related occurrence or clinical incident has taken place involving one or more entities.
-
E.
clinicalSignOf
Indicates that one clinical sign is evidence or manifestation of a particular disease, condition, or underlying medical 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3960fb481909c90d6d6cafc6222 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06ace53081909b5f81f382f6591e |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:34 p.m.