Triple
T29629342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHIR |
E755533
|
entity |
| Predicate | resourceExamples |
P58841
|
FINISHED |
| Object | Patient |
—
|
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: Patient | Statement: [FHIR, resourceExamples, Patient]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resourceExamples Context triple: [FHIR, resourceExamples, Patient]
-
A.
baseExamples
Indicates that something serves as a fundamental or illustrative example for understanding or demonstrating another concept, item, or case.
-
B.
toolUseExamples
Indicates that one entity provides example instances or demonstrations of how a particular tool is or can be used by another entity.
-
C.
backendExample
Indicates that something serves as an example or illustrative instance within a backend or server-side context.
-
D.
locationOfExamples
chosen
Indicates that something serves as the place or context where examples of a particular type, concept, or item can be found.
-
E.
responseExample
Indicates that one entity serves as an illustrative or sample response corresponding to another entity (such as a prompt, question, or situation).
- 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_69f0ef88fbe081908f0ad90c1c413f1c |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f66e64ac588190a91481917a6e91da |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:40 p.m.