Triple
T37661763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wither Skeleton Skull |
E937732
|
entity |
| Predicate | luminance |
P55247
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Wither Skeleton Skull, luminance, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: luminance Context triple: [Wither Skeleton Skull, luminance, 0]
-
A.
luminanceRange
Indicates the span between the minimum and maximum luminance (brightness) values associated with an entity or visual element.
-
B.
relativeLuminance
chosen
Indicates the measured brightness of one entity relative to a reference or to other entities in the same context.
-
C.
designLuminosity
Indicates the specified luminosity level or brightness characteristics that something is designed or intended to have.
-
D.
hasLightness
Indicates that one entity possesses or exhibits a certain degree or quality of lightness (such as brightness or value) in relation to another.
-
E.
brightnessCorrelatesWith
Indicates that changes in the brightness of one entity are systematically associated with changes in the brightness of another 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.