Triple
T3814664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytona International Speedway |
E84221
|
entity |
| Predicate | hasNumberOfSuites |
P13078
|
FINISHED |
| Object | 60+ |
—
|
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: 60+ | Statement: [Daytona International Speedway, hasNumberOfSuites, 60+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSuites Context triple: [Daytona International Speedway, hasNumberOfSuites, 60+]
-
A.
numberOfSuites
chosen
Indicates the total count of suites associated with or contained within a given entity.
-
B.
numberOfTests
Indicates the quantity of tests associated with or performed in a given context or entity.
-
C.
testSuite
Indicates that one entity is a collection or grouping of tests designed to be executed together, typically to validate behavior or functionality.
-
D.
plannedNumberOfTests
Indicates the total count of tests that are intended or scheduled to be conducted for a given context or period.
-
E.
hasParallelReporter
Indicates that a legal case or decision has an alternative citation or report in a different reporter series that runs in parallel to the primary one.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.