Triple
T22356831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phoenix Raceway |
E552674
|
entity |
| Predicate | turnBankingRange |
P133769
|
FINISHED |
| Object | 10–11 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: 10–11 degrees | Statement: [Phoenix Raceway, turnBankingRange, 10–11 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnBankingRange Context triple: [Phoenix Raceway, turnBankingRange, 10–11 degrees]
-
A.
turnBanking
Indicates that an entity is executing a turning maneuver that involves banking or tilting laterally, typically as part of directional change.
-
B.
hasBankingInTurns
Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
-
C.
bankingInTurns
Indicates that entities are taking alternating roles or actions in a banking-related context, with each one acting in turn rather than simultaneously.
-
D.
cardNumbersRange
Indicates that the associated entity or context involves a range of card numbers spanning from a specified lower bound to a specified upper bound.
-
E.
bankingTurnsDegrees
chosen
Indicates that an entity is tilting or banking by a specified number of degrees relative to a reference orientation.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157d08b148190a9a4e445e8579219 |
completed | April 29, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:44 p.m.