Triple
T29086655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHIR PractitionerRole |
E734133
|
entity |
| Predicate | linksPractitionerTo |
P165988
|
FINISHED |
| Object | Organization |
—
|
NE NERFINISHED |
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: Organization | Statement: [FHIR PractitionerRole, linksPractitionerTo, Organization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linksPractitionerTo Context triple: [FHIR PractitionerRole, linksPractitionerTo, Organization]
-
A.
associatedWithPractice
Indicates a relationship in which an entity is connected or linked to a particular practice, activity, or customary way of doing something.
-
B.
linkedPractice
Indicates that one practice is associated or connected to another practice in a meaningful or relevant way.
-
C.
practitionerType
Indicates the specific category or role of practitioner associated with an entity (e.g., doctor, nurse, therapist).
-
D.
officeFollowedInPracticeBy
Indicates that one office or position is typically succeeded or implemented in practice by another office or position, even if not formally designated as its successor.
-
E.
notablePractitioner
Indicates that an entity is a well-known or distinguished practitioner of a particular field, discipline, or activity.
- 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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f66147dd648190893f33542d8d0155 |
completed | May 2, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 11:01 a.m.