Triple
T13290770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1950 Formula One World Championship |
E316553
|
entity |
| Predicate | fastestLapBonusPoints |
P109349
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1950 Formula One World Championship, fastestLapBonusPoints, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fastestLapBonusPoints Context triple: [1950 Formula One World Championship, fastestLapBonusPoints, 1]
-
A.
fastestLapLapNumber
Indicates the specific lap number on which the fastest lap was achieved in a race.
-
B.
fastestLapTime
Indicates the shortest recorded time an entity achieved to complete a single lap in a given context or event.
-
C.
grandPrixFastestLaps
Indicates the relationship where a driver records the fastest lap time during a specific Grand Prix race.
-
D.
fastestLapTeam
Indicates that a team recorded the fastest lap time in a given race or session.
-
E.
winnerLaps
Indicates that one participant completed more laps than another, thereby winning based on lap count.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:27 p.m.