Triple
T32510489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MinuteClinic |
E830916
|
entity |
| Predicate | healthcareProfessionalType |
P140593
|
FINISHED |
| Object | nurse practitioners |
—
|
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: nurse practitioners | Statement: [MinuteClinic, healthcareProfessionalType, nurse practitioners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthcareProfessionalType Context triple: [MinuteClinic, healthcareProfessionalType, nurse practitioners]
-
A.
practitionerType
chosen
Indicates the specific category or role of practitioner associated with an entity (e.g., doctor, nurse, therapist).
-
B.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
C.
clinicalRole
Indicates the specific function, responsibility, or position an entity holds within a clinical or healthcare context.
-
D.
medicalQualificationFrom
Indicates that a person or medical professional obtained their medical qualification or degree from a specified institution or source.
-
E.
usedMedicalPersonnel
Indicates that an entity employed or made use of medical personnel in performing an action or providing a service.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c497459081908caefb70f03ee38d |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1 a.m.