Triple
T28872617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHIR Patient |
E732177
|
entity |
| Predicate | hasFHIRVersion |
P55140
|
FINISHED |
| Object | DSTU2 |
—
|
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: DSTU2 | Statement: [FHIR Patient, hasFHIRVersion, DSTU2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFHIRVersion Context triple: [FHIR Patient, hasFHIRVersion, DSTU2]
-
A.
hasVersionIn
Indicates that one entity exists as a specific version or variant within the context, format, or system represented by another entity.
-
B.
hasVersionStatus
Indicates that an entity is associated with a particular version state or status within its lifecycle or revision history.
-
C.
supportsSpecificationVersion
chosen
Indicates that one entity is compatible with and able to operate according to a particular version of a specification.
-
D.
hasVersionNumber
Indicates that an entity is associated with a specific version identifier or number.
-
E.
hasStandardVersion
Indicates that one entity serves as the official or canonical version of another entity.
- 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_69f05b06807c81909b4bbd4c20403a2b |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 7:34 a.m.