Triple
T27662431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chubby |
E697154
|
entity |
| Predicate | coordinationGranularity |
P167783
|
FINISHED |
| Object | coarse-grained |
—
|
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: coarse-grained | Statement: [Chubby, coordinationGranularity, coarse-grained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coordinationGranularity Context triple: [Chubby, coordinationGranularity, coarse-grained]
-
A.
granularityLevel
Indicates the degree of detail or resolution at which something is specified, measured, or analyzed within a given context.
-
B.
controlGranularity
Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
-
C.
allocationGranularity
Indicates the size or unit in which a resource or memory region is divided and assigned during allocation.
-
D.
executionGranularity
Indicates the level of detail or subdivision at which an operation, task, or process is carried out or controlled.
-
E.
scalingGranularity
Indicates the level of detail or resolution at which a quantity, process, or system is adjusted or scaled.
- F. None of above. chosen
Provenance (4 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f66cf092c881908d7034c9c2bc61d5 |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 27, 2026, 2:37 p.m.