Triple
T35260349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddington A |
E1018352
|
entity |
| Predicate | hasLowAlbedo |
P198949
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Eddington A, hasLowAlbedo, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowAlbedo Context triple: [Eddington A, hasLowAlbedo, true]
-
A.
hasHighAlbedo
Indicates that the subject reflects a large proportion of incoming light or radiation from its surface.
-
B.
albedoType
Indicates the type or classification of an object's albedo, specifying the nature or category of its reflectivity characteristics.
-
C.
hasLowerSurfaceTemperatureThan
Indicates that the surface temperature of one entity is lower than the surface temperature of another entity.
-
D.
hasLowLuminosity
Indicates that an entity emits relatively little light or energy compared to a typical or reference level.
-
E.
hasAlbedo
Indicates that an entity possesses a specific reflectivity or albedo value, describing how much incoming light it reflects.
- 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_69f76de4be5c8190a51705c07612cac8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
| PDg | Predicate description generation | batch_69ff167608f08190b7cd2cf65ddecbf3 |
completed | May 9, 2026, 11:11 a.m. |
Created at: May 3, 2026, 4:02 p.m.