Triple
T6831964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Fork Canyon |
E157157
|
entity |
| Predicate | feeArea |
P72921
|
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: [American Fork Canyon, feeArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feeArea Context triple: [American Fork Canyon, feeArea, yes]
-
A.
fareArea
Indicates the geographic or zonal region within which a particular fare or pricing rule applies.
-
B.
venueArea
Indicates the physical size or spatial extent of a venue, typically measured in units such as square meters or square feet.
-
C.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
-
D.
franchiseArea
Indicates the geographic region or territory within which a franchisee is authorized to operate under a franchising agreement.
-
E.
feeType
Indicates the specific category or classification of a fee associated with a transaction, service, or obligation.
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62992908190996efab71cbf70f0 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d11fab808190b18160ff3829fcc6 |
completed | March 27, 2026, 6:49 p.m. |
Created at: March 27, 2026, 2:18 p.m.