Triple
T706695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytona Beach |
E14114
|
entity |
| Predicate | drivingOnBeach |
P246
|
FINISHED |
| Object | permitted in designated areas |
—
|
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: permitted in designated areas | Statement: [Daytona Beach, drivingOnBeach, permitted in designated areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingOnBeach Context triple: [Daytona Beach, drivingOnBeach, permitted in designated areas]
-
A.
drivesOn
chosen
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
B.
drives
Indicates that one entity operates and controls the movement of a vehicle or similar conveyance transporting themselves or others.
-
C.
hasBeach
Indicates that one entity possesses, includes, or is characterized by a beach as part of its features or environment.
-
D.
driveType
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
E.
hasScenicDrive
Indicates that one entity offers or features a visually appealing or picturesque driving route associated with it.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.