Triple
T22997840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kappa Orionis |
E572550
|
entity |
| Predicate | opticalColor |
P32006
|
FINISHED |
| Object | blue-white |
—
|
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: blue-white | Statement: [Kappa Orionis, opticalColor, blue-white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opticalColor Context triple: [Kappa Orionis, opticalColor, blue-white]
-
A.
opticalSize
Indicates that one entity has a particular visual or perceived size relative to another, often dependent on viewing conditions or context.
-
B.
opticalProperty
chosen
Indicates a relationship where an entity has or is characterized by a specific optical property, such as how it interacts with or responds to light.
-
C.
laserColor
Indicates the color attribute associated with a laser in the relationship or action.
-
D.
hasOpticalElement
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
-
E.
cereColor
Indicates that one entity specifies or denotes the color of another entity’s cere (the fleshy area above a bird’s beak).
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f452b48190951fc5dde56c1bb2 |
completed | April 29, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.