Triple
T28991097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 São Paulo Grand Prix qualifying |
E736026
|
entity |
| Predicate | secondPlaceDriverInQualifying |
P29125
|
FINISHED |
| Object | George Russell |
—
|
NE NERFINISHED |
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: George Russell | Statement: [2022 São Paulo Grand Prix qualifying, secondPlaceDriverInQualifying, George Russell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPlaceDriverInQualifying Context triple: [2022 São Paulo Grand Prix qualifying, secondPlaceDriverInQualifying, George Russell]
-
A.
secondPlaceDriverNationality
Indicates the nationality of the driver who finished in second place in a given race or event.
-
B.
secondRunnerUp
Indicates that one entity finished in third place in a competition or ranking relative to the others.
-
C.
secondPlaceTime
Indicates the time at which an entity achieved second place in a ranked event or competition.
-
D.
secondPlace
chosen
Indicates that an entity holds the position of runner-up or finishes in second place in a ranked ordering, competition, or comparison relative to others.
-
E.
secondRoundRunnerUp
Indicates that an entity finished in third place (runner-up to the runner-up) in the second round of a competition or selection process.
- 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_69f077eacd0481908ef0bafd74491cd0 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 28, 2026, 9:25 a.m.