Triple
T18016108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOCSegmentation |
E431001
|
entity |
| Predicate | hasAnnotationGranularity |
P109501
|
FINISHED |
| Object | pixel-level |
—
|
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: pixel-level | Statement: [VOCSegmentation, hasAnnotationGranularity, pixel-level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAnnotationGranularity Context triple: [VOCSegmentation, hasAnnotationGranularity, pixel-level]
-
A.
granularityLevel
chosen
Indicates the degree of detail or resolution at which something is specified, measured, or analyzed within a given context.
-
B.
hasFineGrainedClasses
Indicates that an entity is associated with or categorized into more detailed, specific subclasses within a broader classification.
-
C.
controlGranularity
Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
-
D.
accessGranularity
Indicates the level of detail or scope at which access or permissions are defined and applied within a system or resource.
-
E.
securityGranularity
Indicates the level of detail or specificity at which security controls, permissions, or protections are defined and applied within a system or context.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.