Triple
T22757061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1980 Firecracker 400 |
E562874
|
entity |
| Predicate | polePositionCarNumber |
P149616
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [1980 Firecracker 400, polePositionCarNumber, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: polePositionCarNumber Context triple: [1980 Firecracker 400, polePositionCarNumber, 27]
-
A.
polePositions
Indicates that one entity holds the pole position (starting first) relative to another entity in a competitive event, such as a race.
-
B.
polePositionDriverTeam
Indicates which team the driver who secured pole position in a race was driving for.
-
C.
championshipCarNumber
Indicates the specific car number associated with a championship-winning entry in a racing competition.
-
D.
polePositionDriverNationality
Indicates the nationality associated with the driver who secured pole position in a race.
-
E.
raceNumberAtTrack
Indicates the specific ordinal number assigned to a race within the sequence of races held at a particular track.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a798ae08190b9810bf241613198 |
completed | April 29, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:25 p.m.