Triple
T9684827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bristol Motor Speedway |
E234378
|
entity |
| Predicate | hasBanking |
P89618
|
FINISHED |
| Object | highly banked turns |
—
|
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: highly banked turns | Statement: [Bristol Motor Speedway, hasBanking, highly banked turns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBanking Context triple: [Bristol Motor Speedway, hasBanking, highly banked turns]
-
A.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
B.
hasFinancialInstitution
Indicates that one entity is associated with or linked to a financial institution, such as a bank or similar financial service provider.
-
C.
hasBankType
Indicates that an entity is associated with or classified by a particular type or category of bank.
-
D.
hasBankingInTurns
Indicates that an entity participates in banking activities that occur in discrete, alternating turns rather than continuously.
-
E.
hasBankingOnApron
Indicates that an entity (such as a structure or platform) has a banking or sloped edge feature present on its apron area.
- 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_69ca84ca73208190957a900c8543bdcc |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9cd0877c81909fde1989d946aae9 |
completed | April 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd9408c848190b84dd74d87f76273 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:16 p.m.