Triple
T30314988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IOWorkLoop |
E771035
|
entity |
| Predicate | schedulingGranularity |
P83651
|
FINISHED |
| Object | event source callbacks |
—
|
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: event source callbacks | Statement: [IOWorkLoop, schedulingGranularity, event source callbacks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schedulingGranularity Context triple: [IOWorkLoop, schedulingGranularity, event source callbacks]
-
A.
executionGranularity
Indicates the level of detail or subdivision at which an operation, task, or process is carried out or controlled.
-
B.
scalingGranularity
Indicates the level of detail or resolution at which a quantity, process, or system is adjusted or scaled.
-
C.
controlGranularity
chosen
Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
-
D.
reservationGranularity
Indicates the level of detail or unit (such as time, quantity, or capacity) at which a reservation can be specified or managed.
-
E.
allocationGranularity
Indicates the size or unit in which a resource or memory region is divided and assigned during allocation.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6816f2070819084042f987b1be68f |
completed | May 2, 2026, 10:57 p.m. |
| PD | Predicate disambiguation | batch_69f67603526c81908295a1ece8727c66 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:51 p.m.