Triple
T20479558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerealia Tholus |
E502414
|
entity |
| Predicate | hasReflectance |
P2046
|
FINISHED |
| Object | higher than average Ceres surface |
—
|
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: higher than average Ceres surface | Statement: [Cerealia Tholus, hasReflectance, higher than average Ceres surface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReflectance Context triple: [Cerealia Tholus, hasReflectance, higher than average Ceres surface]
-
A.
hasAlbedo
chosen
Indicates that an entity possesses a specific reflectivity or albedo value, describing how much incoming light it reflects.
-
B.
hasMirrorOrLensMaterial
Indicates that an object’s mirror or lens component is made from a specified material.
-
C.
opticalProperty
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.
-
D.
hasReflectionFormula
Indicates that an entity is associated with a specific formula or expression used to compute its reflection (e.g., across a line, plane, or axis).
-
E.
refractiveIndex
Indicates the ratio describing how much light slows down and bends when passing through a given medium compared to in a vacuum.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b55d7a881909dfe3ea0e74b742b |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e5768372988190b08ef8ae67d42ab6 |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:34 a.m.