Triple
T38340324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chili Bowl Nationals |
E1038078
|
entity |
| Predicate | approximateEntriesPerYear |
P197177
|
FINISHED |
| Object | over 300 cars |
—
|
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: over 300 cars | Statement: [Chili Bowl Nationals, approximateEntriesPerYear, over 300 cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateEntriesPerYear Context triple: [Chili Bowl Nationals, approximateEntriesPerYear, over 300 cars]
-
A.
hasNumberOfOccurrencesPerYear
chosen
Indicates the relationship that specifies how many times something happens within a one-year period.
-
B.
hasApproximateCountInHumans
Indicates that an entity is associated with an estimated or approximate numerical count specifically in humans.
-
C.
approximateTimeInYear
Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
-
D.
numberOfReleasesPerYear
Indicates the quantity of releases that occur within a single year.
-
E.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fffc783b648190bcd7df017514d206 |
completed | May 10, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69fffc03fa24819099e12413dc6e0afd |
completed | May 10, 2026, 3:31 a.m. |
Created at: May 3, 2026, 4:30 p.m.