Triple
T27855710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haddenham and Thame Parkway |
E704077
|
entity |
| Predicate | hasAccessibleParking |
P171436
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Haddenham and Thame Parkway, hasAccessibleParking, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccessibleParking Context triple: [Haddenham and Thame Parkway, hasAccessibleParking, true]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
C.
hasStreetParking
Indicates that a location or property offers parking spaces available on the adjacent street.
-
D.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
E.
isAccessibleForFreeParking
Indicates that a location or facility can be used for parking without any cost.
- 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_69ef840e614c8190a88cf9638c14a265 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 6:14 p.m.