Triple
T18915315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homestead-Miami Speedway |
E462709
|
entity |
| Predicate | trackLengthOvalMiles |
P26813
|
FINISHED |
| Object | 1.5 |
—
|
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: 1.5 | Statement: [Homestead-Miami Speedway, trackLengthOvalMiles, 1.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackLengthOvalMiles Context triple: [Homestead-Miami Speedway, trackLengthOvalMiles, 1.5]
-
A.
approximateLengthInMiles
chosen
Indicates the estimated distance or extent of something measured in miles.
-
B.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
C.
raceDistanceType
Indicates the specific type or category of distance over which a race is conducted.
-
D.
raceDistanceApprox
Indicates that the distance of a race is approximately equal to a specified value, allowing for some margin of error rather than requiring an exact match.
-
E.
perimeterRunningTrackLength
Indicates the length of a running track that follows the perimeter of a given area or facility.
- 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_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. |
Created at: April 10, 2026, 11:58 a.m.