Triple
T29629396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FHIR |
E755533
|
entity |
| Predicate | typicalSerialization |
P77670
|
FINISHED |
| Object | JSON |
—
|
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: JSON | Statement: [FHIR, typicalSerialization, JSON]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSerialization Context triple: [FHIR, typicalSerialization, JSON]
-
A.
originalSerialization
Indicates that one entity is the initial or source serialized form from which another serialized representation is derived.
-
B.
supportsSerialization
Indicates that an entity is capable of being converted to and from a serialized form for storage or transmission.
-
C.
primarySerialization
chosen
Indicates that one representation or format of an entity is designated as its main or default form for storage, transmission, or processing.
-
D.
hasSerialization
Indicates that one entity is represented, encoded, or stored as a serialized form in another entity.
-
E.
serializationExample
Indicates that one entity serves as an example or illustration of how another entity is serialized or converted into a serial form.
- 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_6a0204dafcc08190868a6f3eab162505 |
completed | May 11, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a0202dc60348190a140bb9da906f5b6 |
completed | May 11, 2026, 4:25 p.m. |
Created at: April 28, 2026, 6:40 p.m.