Triple
T7408845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odysseus impact basin |
E170947
|
entity |
| Predicate | albedoContrast |
P76599
|
FINISHED |
| Object | moderate |
—
|
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: moderate | Statement: [Odysseus impact basin, albedoContrast, moderate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: albedoContrast Context triple: [Odysseus impact basin, albedoContrast, moderate]
-
A.
hasAlbedo
Indicates that an entity possesses a specific reflectivity or albedo value, describing how much incoming light it reflects.
-
B.
createsContrastIn
Indicates a relationship where one element is used to highlight or emphasize differences with another element within a given context.
-
C.
registerContrast
Indicates that an entity records or establishes a distinction or difference between two or more items or states.
-
D.
themeContrast
Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
-
E.
contrastRatio
Indicates the proportional difference in luminance or intensity between two visual elements being compared.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f29acf588190a7c4056bdc4f3ffc |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f15c36d48190bc75353d3f67555a |
completed | March 27, 2026, 9:06 p.m. |
Created at: March 27, 2026, 3:10 p.m.