Triple
T1954148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vienna/Fairfax–GMU station |
E42225
|
entity |
| Predicate | hasKissAndRide |
P33499
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Vienna/Fairfax–GMU station, hasKissAndRide, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKissAndRide Context triple: [Vienna/Fairfax–GMU station, hasKissAndRide, yes]
-
A.
hasParkAndRideFunction
Indicates that a location or facility serves as a park-and-ride, where people can park vehicles and transfer to another mode of transport for the rest of their journey.
-
B.
hasFormOfPublicTransit
Indicates that one entity provides or is associated with a particular type or mode of public transportation for another entity or context.
-
C.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
D.
hasPublicTransitRole
Indicates that an entity holds a specific functional role or responsibility within a public transit system.
-
E.
hasShuttleLine
Indicates that there is a shuttle service or route operating between the related entities.
- F. None of above. chosen
Provenance (4 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb351c148819080173c09876e814a |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb1ddccbc8190bf2bd8bac673c0c5 |
completed | March 7, 2026, 5:04 a.m. |
Created at: March 4, 2026, 7:36 p.m.