Triple
T8624158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sikorsky (crater) |
E204241
|
entity |
| Predicate | hasInteriorCondition |
P6655
|
FINISHED |
| Object | relatively level floor with small craters |
—
|
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: relatively level floor with small craters | Statement: [Sikorsky (crater), hasInteriorCondition, relatively level floor with small craters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteriorCondition Context triple: [Sikorsky (crater), hasInteriorCondition, relatively level floor with small craters]
-
A.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
B.
hasInteriorColor
Indicates that an entity possesses a specific color used on its interior surfaces or internal parts.
-
C.
hasExteriorType
Indicates that an entity possesses a specific kind or style of exterior.
-
D.
hasAirConditioning
Indicates that an entity is equipped with or provides air conditioning.
-
E.
interiorStyle
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:26 p.m.