Triple
T815729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia |
E17648
|
entity |
| Predicate | hasExecutionModel |
P5328
|
FINISHED |
| Object | JIT-compiled |
—
|
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: JIT-compiled | Statement: [Julia, hasExecutionModel, JIT-compiled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExecutionModel Context triple: [Julia, hasExecutionModel, JIT-compiled]
-
A.
executionModel
chosen
Indicates how a process, task, or operation is carried out or implemented, specifying the underlying method, strategy, or mechanism of its execution.
-
B.
hasExecutor
Indicates that a particular action, task, or legal instrument is carried out or implemented by a specified responsible agent or party.
-
C.
hasAccessModel
Indicates that one entity is permitted to use, interact with, or retrieve a particular model controlled by another entity or system.
-
D.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
-
E.
executedWith
Indicates that an action or process was carried out using, accompanied by, or in conjunction with a specified tool, method, or participant.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab5157b08190b6c8f2fd455f261e |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa756920819080ae82948974c876 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.