Triple
T18956615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Maria Rupes |
E463795
|
entity |
| Predicate | hasPlanetaryBodyType |
P62445
|
FINISHED |
| Object | terrestrial planet surface feature |
—
|
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: terrestrial planet surface feature | Statement: [Santa Maria Rupes, hasPlanetaryBodyType, terrestrial planet surface feature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlanetaryBodyType Context triple: [Santa Maria Rupes, hasPlanetaryBodyType, terrestrial planet surface feature]
-
A.
hasPlanetaryFeatureType
chosen
Indicates that an entity possesses or is associated with a specific type of planetary surface or geological feature.
-
B.
orbitalBodyType
Indicates the classification of an orbital body in terms of its type (e.g., planet, moon, asteroid, comet) within an orbital system.
-
C.
hasBodyPlanType
Indicates that an organism possesses a particular overall structural or morphological body plan type.
-
D.
hasPlanet
Indicates that one entity possesses, contains, or is associated with a particular planet as part of its system or domain.
-
E.
hasDwarfPlanet
Indicates that one entity possesses or is associated with a dwarf planet as part of its system or domain.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5cdf2d08190a0aecd3fa5335a75 |
completed | April 20, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon