Triple
T28107443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanoi Street Circuit layout (Vietnam Grand Prix) |
E710400
|
entity |
| Predicate | approximateNumberOfCorners |
P109332
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Hanoi Street Circuit layout (Vietnam Grand Prix), approximateNumberOfCorners, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfCorners Context triple: [Hanoi Street Circuit layout (Vietnam Grand Prix), approximateNumberOfCorners, 23]
-
A.
hasCornerCount
chosen
Indicates that an entity is associated with a specific number of corners.
-
B.
tracksPerCorner
Indicates the number of distinct tracks or lanes associated with each corner in a layout or design.
-
C.
hasApproximateNumberOfPieces
Indicates that an entity is associated with an estimated or non-exact count of pieces or components.
-
D.
hasSlowCorners
Indicates that an entity possesses corners or turning points that are navigated or traversed at a relatively low speed.
-
E.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 27, 2026, 9:09 p.m.