Triple
T12864056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Wilkesboro, North Carolina |
E307669
|
entity |
| Predicate | hasNASCARHistory |
P8241
|
FINISHED |
| Object | early NASCAR venue |
—
|
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: early NASCAR venue | Statement: [North Wilkesboro, North Carolina, hasNASCARHistory, early NASCAR venue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNASCARHistory Context triple: [North Wilkesboro, North Carolina, hasNASCARHistory, early NASCAR venue]
-
A.
NASCARCupSeriesWins
Indicates the number of NASCAR Cup Series races that a given driver, team, or entity has won.
-
B.
NASCARTeamOwned
Indicates that a particular NASCAR team is owned or possessed by a specified owner entity.
-
C.
hasHistoricFranchise
Indicates that an entity is associated with or possesses a franchise that has historical significance or longstanding legacy.
-
D.
Daytona500Wins
Indicates that the subject has won the Daytona 500 race the specified number of times or in the specified instances.
-
E.
hasMotorsportInvolvement
chosen
Indicates that an entity is involved in motorsport, such as through participation, organization, sponsorship, or other direct association with motor racing activities.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:37 p.m.