Triple
T28872504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHIR Binary |
E732175
|
entity |
| Predicate | hasFHIRResourceTypeCode |
P3729
|
FINISHED |
| Object | Binary |
—
|
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: Binary | Statement: [FHIR Binary, hasFHIRResourceTypeCode, Binary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFHIRResourceTypeCode Context triple: [FHIR Binary, hasFHIRResourceTypeCode, Binary]
-
A.
hasTypeCode
Indicates that an entity is associated with a specific type classification represented by a code.
-
B.
hasTypeOfResource
chosen
Indicates that an entity is associated with a specific category or kind of resource it represents or utilizes.
-
C.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
D.
hasKeyPractitionerType
Indicates that an entity is associated with a specific primary or principal type of practitioner involved with it.
-
E.
hasICD10Code
Indicates that an entity is associated with a specific ICD-10 diagnostic code used for classifying diseases and health conditions.
- 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_69f65a47793481908efd891e27e541bf |
completed | May 2, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 7:34 a.m.