Triple
T35330345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eldora Speedway |
E1020298
|
entity |
| Predicate | hasHighBanking |
P199547
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Eldora Speedway, hasHighBanking, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighBanking Context triple: [Eldora Speedway, hasHighBanking, true]
-
A.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
B.
hasBankOn
Indicates that one entity is located on or alongside the bank (edge) of another entity, typically a river, lake, or similar body.
-
C.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
D.
hasFinancialInstitution
Indicates that one entity is associated with or linked to a financial institution, such as a bank or similar financial service provider.
-
E.
hasBankingSpecialty
Indicates that an entity possesses a specific area of expertise or specialization within the field of banking.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
| PDg | Predicate description generation | batch_69ff4163a8548190b0eaafd0a377b141 |
completed | May 9, 2026, 2:14 p.m. |
Created at: May 3, 2026, 4:03 p.m.