Triple
T26657975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | camelback hills |
E666562
|
entity |
| Predicate | effectOnRiders |
P118952
|
FINISHED |
| Object | weightlessness |
—
|
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: weightlessness | Statement: [camelback hills, effectOnRiders, weightlessness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnRiders Context triple: [camelback hills, effectOnRiders, weightlessness]
-
A.
numberOfRiders
Indicates the total count of riders associated with a given entity or event.
-
B.
intendedRiderExperience
chosen
Indicates the type or quality of experience that is planned or designed for a rider in the context of a ride or transportation service.
-
C.
riderType
Indicates the category or role of a rider in relation to a ride, transport service, or vehicle (e.g., passenger, driver, courier).
-
D.
primaryRiders
Indicates that the referenced entities are the main or principal riders associated with a particular vehicle, trip, or ride-related event.
-
E.
ridershipLevel
Indicates the magnitude or intensity of usage by riders or passengers for a given service, route, or system.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 2:35 a.m.