Triple
T22800640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darlington Raceway |
E564379
|
entity |
| Predicate | hasBankingOnFrontStretch |
P55734
|
FINISHED |
| Object | 3–5 degrees |
—
|
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: 3–5 degrees | Statement: [Darlington Raceway, hasBankingOnFrontStretch, 3–5 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBankingOnFrontStretch Context triple: [Darlington Raceway, hasBankingOnFrontStretch, 3–5 degrees]
-
A.
frontstretchBanking
chosen
Indicates the degree or characteristics of the banking (incline or slope) along the frontstretch portion of a racetrack.
-
B.
hasBankingOnApron
Indicates that an entity (such as a structure or platform) has a banking or sloped edge feature present on its apron area.
-
C.
hasBankOn
Indicates that one entity is located on or alongside the bank (edge) of another entity, typically a river, lake, or similar body.
-
D.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
E.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdc72908190827c9e36a498dc97 |
completed | April 29, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:31 p.m.