Triple
T35795300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1950 British Grand Prix |
E1034814
|
entity |
| Predicate | carsEntered |
P22510
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [1950 British Grand Prix, carsEntered, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carsEntered Context triple: [1950 British Grand Prix, carsEntered, 21]
-
A.
enteredTraffic
Indicates that an entity has moved into or joined a flow of traffic, such as entering a roadway or traffic stream.
-
B.
enteredTrafficOn
Indicates that an entity moved from a non-traffic context (e.g., driveway, ramp, side road) into an active traffic flow or roadway.
-
C.
enteredTrafficWith
Indicates that an entity moved into or joined a flow of traffic, transitioning from a non-traffic state or area into active traffic.
-
D.
numberOfVehicles
chosen
Indicates the total count of vehicles associated with a given entity or context.
-
E.
hasVehicleCrossing
Indicates that a location or route includes a designated crossing point specifically intended for vehicles to pass through.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a25431b481908e39e953b207b6be |
completed | May 3, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.