Triple
T6172871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Prix of Long Beach |
E137744
|
entity |
| Predicate | turnCount |
P30551
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Grand Prix of Long Beach, turnCount, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnCount Context triple: [Grand Prix of Long Beach, turnCount, 11]
-
A.
numberOfTurns
chosen
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
B.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
C.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
D.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
E.
movementNumber
Indicates the specific sequential position of a movement within a larger multi-movement work or performance.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d9319548190980c99f692bd4115 |
completed | March 22, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69c055f7f12881908e21c04e9b752ba4 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.