Triple
T8418803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Integrating the Healthcare Enterprise |
E198795
|
entity |
| Predicate | usesStandard |
P1587
|
FINISHED |
| Object | FHIR |
E702955
|
NE 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: FHIR | Statement: [Integrating the Healthcare Enterprise, usesStandard, FHIR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FHIR Context triple: [Integrating the Healthcare Enterprise, usesStandard, FHIR]
-
A.
FHIR R5 (preview)
chosen
FHIR R5 (preview) is the upcoming fifth major release of the HL7 Fast Healthcare Interoperability Resources standard, offering enhanced data models and interoperability features for exchanging healthcare information.
-
B.
FHIR STU3
FHIR STU3 is the third major release of the HL7 Fast Healthcare Interoperability Resources standard, defining structured formats and APIs for exchanging electronic healthcare data.
-
C.
HL7 standards
HL7 standards are a widely adopted set of international specifications for the exchange, integration, sharing, and retrieval of electronic health information between healthcare systems.
-
D.
HL7 International
HL7 International is a global standards organization that develops and promotes frameworks and specifications for the exchange, integration, sharing, and retrieval of electronic health information.
-
E.
OpenMRS
OpenMRS is an open-source medical record system platform widely used in resource-constrained settings to improve healthcare delivery and data management.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c7d6e48190a2bbde89c5d42af6 |
completed | March 31, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce03476b288190b3df8f9f4d502ea8 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:06 p.m.