Triple
T5363436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nunki |
E103073
|
entity |
| Predicate | hasUminusBColorIndex |
P63031
|
FINISHED |
| Object | ~−0.88 |
—
|
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: ~−0.88 | Statement: [Nunki, hasUminusBColorIndex, ~−0.88]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUminusBColorIndex Context triple: [Nunki, hasUminusBColorIndex, ~−0.88]
-
A.
hasComplementaryColor
Indicates that one color is the complementary (i.e., opposite on the color wheel, providing maximum contrast) counterpart of another color.
-
B.
colorIndexB−V
Indicates the difference between an object's blue (B) and visual (V) magnitudes, representing its color and thus its temperature or spectral characteristics.
-
C.
hasColorSymbol
Indicates that one entity is associated with another entity that serves as its representative or symbolic color.
-
D.
hasColorExcess
Indicates that an entity exhibits a measured amount of color excess, typically representing the difference between its observed color and its intrinsic or expected color.
-
E.
hasColorRange
Indicates that an entity possesses or is associated with a specific span or set of colors, rather than a single discrete color.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865b9b808190a1e8c283ba28d645 |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd85731dcc8190b4c1fe155967ab81 |
completed | March 20, 2026, 5:35 p.m. |
Created at: March 20, 2026, 2:02 p.m.