Triple
T10071864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flushing–Main Street |
E213646
|
entity |
| Predicate | rankByRidership |
P8174
|
FINISHED |
| Object | one of the busiest stations in Queens |
—
|
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: one of the busiest stations in Queens | Statement: [Flushing–Main Street, rankByRidership, one of the busiest stations in Queens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByRidership Context triple: [Flushing–Main Street, rankByRidership, one of the busiest stations in Queens]
-
A.
hasApproxAnnualPassengerUsageRank
chosen
Indicates the approximate position or ranking of an entity based on its annual passenger usage compared to similar entities.
-
B.
annualRidership
Indicates the total number of passengers who use a transportation service over the course of one year.
-
C.
isOneOfBusiestStopsOn
Indicates that a stop ranks among the most heavily used or frequently served stops on a given route or line.
-
D.
rapidTransitSystem
Indicates a transportation relationship where people or goods are moved via a high-capacity, high-frequency public transit system designed for rapid travel over urban or regional routes.
-
E.
rankInNYCAreaByTraffic
Indicates the position of an entity in an ordered list of entities in the New York City area, sorted by the amount of traffic they receive.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd01279388190b94c8def00425c78 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.