Triple
T35632830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castle Shannon, Pennsylvania |
E1029632
|
entity |
| Predicate | hasLightRailParkAndRide |
P24860
|
FINISHED |
| Object | Castle Shannon Park and Ride |
—
|
NE NERFINISHED |
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: Castle Shannon Park and Ride | Statement: [Castle Shannon, Pennsylvania, hasLightRailParkAndRide, Castle Shannon Park and Ride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightRailParkAndRide Context triple: [Castle Shannon, Pennsylvania, hasLightRailParkAndRide, Castle Shannon Park and Ride]
-
A.
hasParkAndRideFunction
chosen
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.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
C.
hasLightRailStationPlanned
Indicates that a light rail station is planned or scheduled to be built at or associated with the given entity.
-
D.
hasParkAndRideGarage
Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
-
E.
hasLightRailInMedian
Indicates that a roadway segment has a light rail line running within its center median.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69feafa1ba0081909013800b85a9f613 |
completed | May 9, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69feae58d62c81909d031f3df8992883 |
completed | May 9, 2026, 3:47 a.m. |
Created at: May 3, 2026, 4:05 p.m.