Triple
T23169463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1975 World 600 |
E578803
|
entity |
| Predicate | lapsPerMile |
P151204
|
FINISHED |
| Object | approximately 266.67 laps per 1000 miles |
—
|
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 266.67 laps per 1000 miles | Statement: [1975 World 600, lapsPerMile, approximately 266.67 laps per 1000 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lapsPerMile Context triple: [1975 World 600, lapsPerMile, approximately 266.67 laps per 1000 miles]
-
A.
trackLengthMiles
Indicates the length of a track measured in miles.
-
B.
typicalRaceDistanceLaps
Indicates the usual number of laps that constitute the standard race distance for a given racing event or category.
-
C.
laps
Indicates that one entity moves around another entity or a course, typically completing a circuit or overtaking it.
-
D.
distancePerLeg
Indicates the distance covered in a single leg or segment of a multi-part journey or route.
-
E.
distancePerRace
Indicates the total distance covered in a single race event or instance.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2e5e208190839ec37de4b974af |
completed | April 29, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:03 p.m.