Triple
T1666076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai International Circuit |
E36014
|
entity |
| Predicate | numberOfTurns |
P30551
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Shanghai International Circuit, numberOfTurns, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTurns Context triple: [Shanghai International Circuit, numberOfTurns, 16]
-
A.
numberOfDraws
Indicates the total count of times an event, game, or contest has ended in a draw or tie.
-
B.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
C.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
D.
movementNumber
Indicates the specific sequential position of a movement within a larger multi-movement work or performance.
-
E.
numberOfWins
Indicates the count of times an entity has achieved victory in a relevant context or competition.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94192abc0819092fc00fef9d53bcb |
completed | March 5, 2026, 8:40 a.m. |
Created at: March 4, 2026, 7:29 p.m.