Triple
T20696733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Space Shot |
E508679
|
entity |
| Predicate | hasRideIntensity |
P141125
|
FINISHED |
| Object | high intensity |
—
|
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: high intensity | Statement: [Space Shot, hasRideIntensity, high intensity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRideIntensity Context triple: [Space Shot, hasRideIntensity, high intensity]
-
A.
hasVehicularActivityLevel
Indicates the degree or intensity of vehicular activity associated with an entity, such as traffic volume or frequency of vehicle use.
-
B.
hasNumberOfRides
Indicates the quantity of rides associated with a given entity.
-
C.
hasRideExperience
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
D.
hasNotableRide
Indicates that an entity is associated with a particularly remarkable or well-known ride or attraction.
-
E.
hasRideMedium
Indicates that an entity’s ride or journey is conducted using a particular transportation medium or mode.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c1123d7c81908a1d16923437266d |
completed | April 21, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c044d1108190b2b5d25de23f6401 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:10 p.m.