Triple
T4775105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skylink people mover system |
E106024
|
entity |
| Predicate | tripTime |
P11363
|
FINISHED |
| Object | about 9 minutes to travel entire loop |
—
|
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 9 minutes to travel entire loop | Statement: [Skylink people mover system, tripTime, about 9 minutes to travel entire loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tripTime Context triple: [Skylink people mover system, tripTime, about 9 minutes to travel entire loop]
-
A.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
B.
travelTimeTypical
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
C.
travelTimeToAirport
Indicates the amount of time required to travel from a given location to an airport.
-
D.
rideDuration
chosen
Indicates the length of time that a ride or trip lasts from start to finish.
-
E.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6584481081908f1041a8827e0b42 |
completed | March 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.