Triple
T3396150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenbelt station |
E71532
|
entity |
| Predicate | hasSurfaceParking |
P3380
|
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: [Greenbelt station, hasSurfaceParking, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceParking Context triple: [Greenbelt station, hasSurfaceParking, yes]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
numberOfParkingSpaces
Indicates the total count of parking spaces associated with a particular entity or location.
-
C.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
D.
parkingType
chosen
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
E.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb856158c81908dd7d3f1f8d6af74 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.