Triple
T23836166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roncevaux Terra |
E590858
|
entity |
| Predicate | albedoCharacteristic |
P131720
|
FINISHED |
| Object | high albedo |
—
|
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: high albedo | Statement: [Roncevaux Terra, albedoCharacteristic, high albedo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: albedoCharacteristic Context triple: [Roncevaux Terra, albedoCharacteristic, high albedo]
-
A.
albedoType
Indicates the type or classification of an object's albedo, specifying the nature or category of its reflectivity characteristics.
-
B.
hasAlbedo
Indicates that an entity possesses a specific reflectivity or albedo value, describing how much incoming light it reflects.
-
C.
hasHighAlbedo
chosen
Indicates that the subject reflects a large proportion of incoming light or radiation from its surface.
-
D.
albedoContrast
Indicates the degree to which two surfaces or regions differ in their reflectivity (albedo), typically highlighting contrast in brightness.
-
E.
hasAlbedoFeatureName
Indicates that an entity has or is associated with a specific named albedo (surface reflectivity) feature.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c882f9148190bb28fe7566ef1e70 |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8:07 p.m.