Triple
T33045282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1969 United States Grand Prix |
E845576
|
entity |
| Predicate | secondPlaceDriverCountry |
P147635
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [1969 United States Grand Prix, secondPlaceDriverCountry, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPlaceDriverCountry Context triple: [1969 United States Grand Prix, secondPlaceDriverCountry, United Kingdom]
-
A.
secondPlaceDriverNationality
chosen
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.
secondPlace
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.
-
D.
coDriversChampionNationality
Indicates the nationality of the co-driver who won the championship.
-
E.
thirdPlaceCoDriver
Indicates that the co-driver finished in third place in a specific event or competition.
- 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fec5c503808190bde0b1829ea43071 |
completed | May 9, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69fec535dd6c8190a6ab85201f5a04a9 |
completed | May 9, 2026, 5:25 a.m. |
Created at: May 1, 2026, 1:24 a.m.