Triple
T26065203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iowa Speedway |
E657380
|
entity |
| Predicate | bankingTurnsMaximum |
P133769
|
FINISHED |
| Object | approximately 14 degrees |
—
|
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: approximately 14 degrees | Statement: [Iowa Speedway, bankingTurnsMaximum, approximately 14 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bankingTurnsMaximum Context triple: [Iowa Speedway, bankingTurnsMaximum, approximately 14 degrees]
-
A.
bankingTurns
Indicates that one entity is making or executing banking turns (coordinated turning maneuvers) relative to another entity or reference frame.
-
B.
bankingInTurns
Indicates that entities are taking alternating roles or actions in a banking-related context, with each one acting in turn rather than simultaneously.
-
C.
hasBankingInTurns
Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
-
D.
bankingTurnsDegrees
chosen
Indicates that an entity is tilting or banking by a specified number of degrees relative to a reference orientation.
-
E.
bankingModel
Indicates the financial or operational framework under which banking activities, services, and relationships are structured and conducted.
- 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_69ee5bbd788481909e22bd7153d0c037 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60696110c8190b48e3769a5836657 |
completed | May 2, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 7:23 p.m.