Triple
T35564123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015 Daytona 500 |
E1027720
|
entity |
| Predicate | scheduledDistanceKm |
P183799
|
FINISHED |
| Object | 804.672 |
—
|
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: 804.672 | Statement: [2015 Daytona 500, scheduledDistanceKm, 804.672]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scheduledDistanceKm Context triple: [2015 Daytona 500, scheduledDistanceKm, 804.672]
-
A.
scheduledDistanceMi
Indicates the planned or expected distance in miles associated with a scheduled event or activity.
-
B.
distanceTraveled
Indicates the total length of the path an entity has moved over a period of time or between two points.
-
C.
trailDistanceContext
Indicates the contextual distance or separation between entities along a trail, path, or route.
-
D.
tourDistanceApproxKm
Indicates an approximate total distance, measured in kilometers, covered during a tour or journey.
-
E.
distanceProvidedBy
Indicates that a specific distance value is supplied or made available by a particular source or provider.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a34e80dc8190980d5b7b0b91341d |
completed | May 3, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:04 p.m.