Triple
T31932760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Food City 500 |
E815297
|
entity |
| Predicate | hostTrackLength |
P134623
|
FINISHED |
| Object | approximately 0.533 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 0.533 miles | Statement: [Food City 500, hostTrackLength, approximately 0.533 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostTrackLength Context triple: [Food City 500, hostTrackLength, approximately 0.533 miles]
-
A.
lapLengthOfTrack
chosen
Indicates the distance or length of a single lap around a track.
-
B.
mainTrackDistance
Indicates the distance measured along the primary or main track between two referenced points or entities.
-
C.
longestTrack
Indicates that the related track is the one with the greatest duration or length among a given set of tracks.
-
D.
notableTrackLength
Indicates that there is a track whose duration is considered significant or noteworthy in the context of the subject.
-
E.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
- 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b2311c7481909fdfa0067f3b5082 |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:04 a.m.