Triple
T5468619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanford station |
E122774
|
entity |
| Predicate | hasVehicleLoadingRamps |
P64257
|
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: [Sanford station, hasVehicleLoadingRamps, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleLoadingRamps Context triple: [Sanford station, hasVehicleLoadingRamps, yes]
-
A.
hasMilitaryRamp
Indicates that a structure or location is equipped with a ramp specifically designed for military use, such as loading, unloading, or deploying military personnel, vehicles, or equipment.
-
B.
hasBusBays
Indicates that a location or facility is equipped with one or more designated bus bays for buses to stop, load, or unload passengers.
-
C.
hasParkingApron
Indicates that a location or facility includes a designated parking apron area for vehicles or aircraft.
-
D.
hasSpiralRampLength
Indicates the length measurement of a spiral-shaped ramp in the relationship.
-
E.
hasIncline
Indicates that one entity possesses or exhibits a slope, tilt, or upward/downward angle relative to another reference.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd927b0b4c81909d5e0f594822e3f9 |
completed | March 20, 2026, 6:31 p.m. |
Created at: March 20, 2026, 2:09 p.m.