Triple
T18915324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homestead-Miami Speedway |
E462709
|
entity |
| Predicate | bankingTurnsDegrees |
P133769
|
FINISHED |
| Object | 18–20 |
—
|
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: 18–20 | Statement: [Homestead-Miami Speedway, bankingTurnsDegrees, 18–20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bankingTurnsDegrees Context triple: [Homestead-Miami Speedway, bankingTurnsDegrees, 18–20]
-
A.
bankingInTurns
Indicates that entities are taking alternating roles or actions in a banking-related context, with each one acting in turn rather than simultaneously.
-
B.
turnBanking
Indicates that an entity is executing a turning maneuver that involves banking or tilting laterally, typically as part of directional change.
-
C.
hasBankingInTurns
Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
-
D.
degreeNumber
Indicates the specific numeric value assigned to a degree, such as its level, rank, or sequence number.
-
E.
degreeForm
Indicates that one entity is the specific academic degree or qualification conferred in the context of another entity (such as a program, award, or credential).
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c62685408190b17280147e1c247a |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:58 a.m.