Triple
T16145789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytona Beach Road Course |
E391776
|
entity |
| Predicate | firstNASCARRaceHeld |
P121307
|
FINISHED |
| Object | 1948 |
—
|
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: 1948 | Statement: [Daytona Beach Road Course, firstNASCARRaceHeld, 1948]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstNASCARRaceHeld Context triple: [Daytona Beach Road Course, firstNASCARRaceHeld, 1948]
-
A.
firstNASCARCupSeriesWin
Indicates the event in which an entity (typically a driver) achieves their first victory in a NASCAR Cup Series race.
-
B.
firstNASCARTruckSeriesWin
Indicates the event in which an entity achieves its first victory in a NASCAR Truck Series race.
-
C.
NASCARCupSeriesStarts
Indicates the number of times an entity has started or participated in NASCAR Cup Series races.
-
D.
firstIndyCarSeriesRace
Indicates the event that was a subject's first race participation in the IndyCar Series.
-
E.
NASCARCupSeriesChampionships
Indicates the number of NASCAR Cup Series championship titles an entity has won.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9376fc8190bd9ef586b00c1d3b |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1835b64948190ae1d2a9d4cc64acf |
completed | April 17, 2026, 12:48 a.m. |
Created at: April 10, 2026, 5:01 a.m.