Triple
T619000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Hinault |
E14468
|
entity |
| Predicate | GiroDItaliaOverallWinsYears |
P16711
|
FINISHED |
| Object | 1980 |
—
|
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: 1980 | Statement: [Bernard Hinault, GiroDItaliaOverallWinsYears, 1980]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GiroDItaliaOverallWinsYears Context triple: [Bernard Hinault, GiroDItaliaOverallWinsYears, 1980]
-
A.
GiroDItaliaWins
Indicates the number of times an entity has won the Giro d'Italia cycling race.
-
B.
TourDeFranceOverallWins
Indicates the number of times an entity has won the overall general classification of the Tour de France.
-
C.
TourDeFranceWins
Indicates the number of times an entity has won the Tour de France cycling race.
-
D.
TourDeFranceWin
Indicates that an entity has won the Tour de France cycling race, typically as the overall general classification winner for a given edition.
-
E.
worldTimeTrialChampion
Indicates that the subject has won a world championship title in an individual time trial cycling event.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfd15288190b4abdbd0bce3edcd |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49d76062c819083ac33f1f87097c7 |
completed | March 1, 2026, 8:11 p.m. |
Created at: March 1, 2026, 7:35 p.m.