Triple
T10651265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Transportation Statistics |
E250974
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | transportation data compendium |
C8739
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: transportation data compendium Context triple: [National Transportation Statistics, instanceOf, transportation data compendium]
-
A.
transportation database
chosen
A transportation database is a structured collection of data that stores, organizes, and manages information related to transportation systems, such as routes, vehicles, schedules, and passenger or cargo records, to support planning, operations, and analysis.
-
B.
transportation index
A transportation index is a composite measure that tracks the performance, activity, or cost trends of the transportation sector (such as shipping, rail, air, and trucking) over time.
-
C.
transportation corridors collection
A transportation corridors collection is an organized set of linear pathways—such as roads, railways, and transit routes—grouped for managing, analyzing, or planning movement across a region.
-
D.
transport model
A transport model is a conceptual or mathematical representation used to simulate and analyze the movement of people, goods, or resources across a network or spatial system under various conditions and constraints.
-
E.
public transport information system
A public transport information system is a software platform that collects, processes, and disseminates real-time and scheduled data about public transit services to passengers, operators, and other stakeholders.
- F. None of above.
Provenance (1 batch)
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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:06 p.m.