Triple
T18741220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michele Mouton |
E458295
|
entity |
| Predicate | worldRallyChampionshipRunnerUp |
P109364
|
FINISHED |
| Object | 1982 |
—
|
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: 1982 | Statement: [Michele Mouton, worldRallyChampionshipRunnerUp, 1982]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldRallyChampionshipRunnerUp Context triple: [Michele Mouton, worldRallyChampionshipRunnerUp, 1982]
-
A.
worldRallyChampionshipTitles
Indicates the number of World Rally Championship titles an entity has won.
-
B.
WRCWins
Indicates that an entity (typically a driver, team, or manufacturer) has achieved one or more victories in World Rally Championship (WRC) events.
-
C.
WorldCupPodiums
Indicates that an entity has achieved a top-three (podium) finish in a FIFA World Cup tournament.
-
D.
WorldCupPodium
Indicates that the entities are the top finishers (e.g., first, second, third place) on the podium of a specific World Cup event.
-
E.
runnerUpDriver
chosen
Indicates that one driver finished in second place relative to others in a race 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5768ecc2081908143310190ffb460 |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:51 a.m.