Triple
T4199627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddy Merckx |
E86034
|
entity |
| Predicate | numberOfVueltaAEspañaWins |
P17169
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Eddy Merckx, numberOfVueltaAEspañaWins, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVueltaAEspañaWins Context triple: [Eddy Merckx, numberOfVueltaAEspañaWins, 1]
-
A.
numberOfVueltaAEspanaOverallVictories
chosen
Indicates the total count of times an entity has won the Vuelta a España general (overall) classification.
-
B.
VueltaAEspanaOverallWinsYears
Indicates the specific years in which an entity won the overall classification of the Vuelta a España.
-
C.
numberOfGrandTourOverallVictories
Indicates the total count of times an entity has won the overall classification in any of cycling’s Grand Tours (Tour de France, Giro d’Italia, or Vuelta a España).
-
D.
TourDeFranceWins
Indicates the number of times an entity has won the Tour de France cycling race.
-
E.
TourDeFranceWin
Indicates that an entity has won the Tour de France cycling race, typically as the overall general classification winner for a given edition.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af036243b4819097efe6b796823cd9 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:49 p.m.