Triple
T16145569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolex 24 at Daytona |
E391771
|
entity |
| Predicate | usesBanking |
P121300
|
FINISHED |
| Object | Daytona tri-oval banking |
—
|
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: Daytona tri-oval banking | Statement: [Rolex 24 at Daytona, usesBanking, Daytona tri-oval banking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBanking Context triple: [Rolex 24 at Daytona, usesBanking, Daytona tri-oval banking]
-
A.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
B.
turnBanking
Indicates that an entity is executing a turning maneuver that involves banking or tilting laterally, typically as part of directional change.
-
C.
offersOnlineBanking
Indicates that a financial institution provides banking services that customers can access and perform over the internet.
-
D.
hasBankingInTurns
Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
-
E.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9376fc8190bd9ef586b00c1d3b |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1835b64948190ae1d2a9d4cc64acf |
completed | April 17, 2026, 12:48 a.m. |
Created at: April 10, 2026, 5:01 a.m.