Triple
T15395058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alberto Contador |
E368156
|
entity |
| Predicate | wonTourDeFranceYear |
P15810
|
FINISHED |
| Object | 2007 |
—
|
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: 2007 | Statement: [Alberto Contador, wonTourDeFranceYear, 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonTourDeFranceYear Context triple: [Alberto Contador, wonTourDeFranceYear, 2007]
-
A.
firstTourDeFranceFinishYear
Indicates the year in which an entity (typically a cyclist) achieved their first finish in the Tour de France.
-
B.
firstTourDeFranceYear
Indicates the year in which an entity (typically a cyclist) first participated in the Tour de France.
-
C.
TourDeFranceWins
Indicates the number of times an entity has won the Tour de France cycling race.
-
D.
TourDeFranceWin
chosen
Indicates that an entity has won the Tour de France cycling race, typically as the overall general classification winner for a given edition.
-
E.
lastTourDeFranceParticipation
Indicates the most recent instance in which an entity took part in the Tour de France.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ac79081908ac79c0b3e7587ff |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.