Triple
T24365003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jules Bianchi |
E614169
|
entity |
| Predicate | bestF1ResultGrandPrix |
P155928
|
FINISHED |
| Object | 2014 Monaco Grand Prix |
—
|
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: 2014 Monaco Grand Prix | Statement: [Jules Bianchi, bestF1ResultGrandPrix, 2014 Monaco Grand Prix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestF1ResultGrandPrix Context triple: [Jules Bianchi, bestF1ResultGrandPrix, 2014 Monaco Grand Prix]
-
A.
bestF1Result
Indicates that one result in a set has the highest F1 score (harmonic mean of precision and recall) compared to all other results.
-
B.
bestFormulaOneChampionshipPosition
Indicates the highest (best) finishing position an entity has ever achieved in a Formula One World Championship season.
-
C.
bestTourDeFranceResult
Indicates the highest (best) finishing position an entity has ever achieved in the Tour de France.
-
D.
F1LapRecordHolder
Indicates that the subject holds the fastest lap record in a Formula 1 race or at a specific Formula 1 circuit.
-
E.
grandPrixWinRate
Indicates the proportion of Grand Prix events that an entity has won relative to the total number of Grand Prix events it has participated in.
- 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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293874f7c8190b472e99640e97f62 |
completed | April 29, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:01 a.m.