Triple
T2629377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenMP |
E59596
|
entity |
| Predicate | usesProgrammingModel |
P21929
|
FINISHED |
| Object | fork-join parallelism |
—
|
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: fork-join parallelism | Statement: [OpenMP, usesProgrammingModel, fork-join parallelism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesProgrammingModel Context triple: [OpenMP, usesProgrammingModel, fork-join parallelism]
-
A.
usedProgramModel
chosen
Indicates that an entity employed a specific program model as the basis or framework for its activities or operations.
-
B.
programUsed
Indicates that a particular program, software, or application was employed or utilized in performing an action or achieving a result.
-
C.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
D.
programmedVia
Indicates that one entity is created, configured, or made to operate through the use of another entity as its programming method, tool, or medium.
-
E.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.