Triple
T19894689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | From the Earth to the Moon |
E478119
|
entity |
| Predicate | timeToMoonInStory |
P137738
|
FINISHED |
| Object | about 97 hours |
—
|
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: about 97 hours | Statement: [From the Earth to the Moon, timeToMoonInStory, about 97 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToMoonInStory Context triple: [From the Earth to the Moon, timeToMoonInStory, about 97 hours]
-
A.
totalEVAOnMoonDuration
Indicates the total amount of time an entity has spent performing extravehicular activities (EVAs) on the Moon.
-
B.
timeOnLunarSurface
Indicates the duration that an entity spends on the surface of the Moon.
-
C.
numberFlownToMoon
Indicates the number of times an entity has traveled to or reached the Moon.
-
D.
earthToMoonRadiusRatio
Indicates the proportional relationship between the radius of the Earth and the radius of the Moon.
-
E.
closestApproachToMoon
Indicates the point or distance at which an object comes nearest to the Moon along its trajectory or orbit.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659105d7481909131d9907ac0094b |
completed | April 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.