Triple
T9185105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Powell & Market cable car turnaround |
E220436
|
entity |
| Predicate | hasBoardingSystem |
P18241
|
FINISHED |
| Object | queue-based boarding |
—
|
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: queue-based boarding | Statement: [Powell & Market cable car turnaround, hasBoardingSystem, queue-based boarding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingSystem Context triple: [Powell & Market cable car turnaround, hasBoardingSystem, queue-based boarding]
-
A.
hasBoardingType
chosen
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
-
B.
hasBoardingOption
Indicates that an entity offers or is associated with a particular way or method by which passengers or items can board or be taken on.
-
C.
hasOnboardSystems
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
-
D.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
E.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc318d5c081908c50b56e5783ea38 |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.