Triple
T9185117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Powell & Market cable car turnaround |
E220436
|
entity |
| Predicate | hasTicketSales |
P60844
|
FINISHED |
| Object | nearby ticket booths and machines |
—
|
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: nearby ticket booths and machines | Statement: [Powell & Market cable car turnaround, hasTicketSales, nearby ticket booths and machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketSales Context triple: [Powell & Market cable car turnaround, hasTicketSales, nearby ticket booths and machines]
-
A.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
ticketsSold
Indicates that a certain number of tickets have been purchased or distributed for a particular event or offering.
-
C.
hasTicketHall
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
-
D.
hasTicketBooths
chosen
Indicates that one entity possesses or contains ticket booths used for selling or distributing tickets.
-
E.
sellsTicketsUnder
Indicates that one entity sells tickets at a price lower than or under the pricing of another entity.
- 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.