Triple
T25932833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SYCL |
E653476
|
entity |
| Predicate | hasProgrammingModelFeature |
P182
|
FINISHED |
| Object | single-source programming model |
—
|
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: single-source programming model | Statement: [SYCL, hasProgrammingModelFeature, single-source programming model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProgrammingModelFeature Context triple: [SYCL, hasProgrammingModelFeature, single-source programming model]
-
A.
hasProgrammingModel
Indicates that one entity defines, specifies, or is associated with the programming model used or supported by another entity.
-
B.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
C.
hasFeature
chosen
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
D.
supportsParallelProgrammingModel
Indicates that one entity provides facilities or mechanisms enabling the use of a parallel programming model with another entity.
-
E.
usesSoftwareModel
Indicates that one entity employs or relies on a particular software model to perform its functions or tasks.
- 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_69e7ab3eb9b881909c1390690551f868 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 22, 2026, 8:37 a.m.