Triple
T6494191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enceladus |
E148113
|
entity |
| Predicate | flybyCountByCassini |
P71057
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Enceladus, flybyCountByCassini, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flybyCountByCassini Context triple: [Enceladus, flybyCountByCassini, 23]
-
A.
numberOfMercuryFlybys
Indicates the number of times a spacecraft or mission performs close flyby encounters with the planet Mercury.
-
B.
numberOfPlannedVenusFlybys
Indicates the total count of Venus flyby maneuvers that are scheduled or intended within a mission plan.
-
C.
flybyOf
Indicates that one entity passes close to another in space without stopping, typically as part of an observational or transit maneuver.
-
D.
firstFlybyBy
Indicates that one entity was the spacecraft, probe, or mission that performed the first flyby of another entity (such as a celestial body or target).
-
E.
flybyDate
Indicates the date on which one object passes close to another in a flyby encounter.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab7c0b8819091437a293b40dfd2 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:53 p.m.