Triple
T15490316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger De Vlaeminck |
E378664
|
entity |
| Predicate | numberOfTirrenoAdriaticoOverallWins |
P118443
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Roger De Vlaeminck, numberOfTirrenoAdriaticoOverallWins, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTirrenoAdriaticoOverallWins Context triple: [Roger De Vlaeminck, numberOfTirrenoAdriaticoOverallWins, 6]
-
A.
numberOfGiroDiLombardiaWins
Indicates the number of times an entity has won the Giro di Lombardia cycling race.
-
B.
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).
-
C.
numberOfMilanSanRemoWins
Indicates the number of times an entity has won the Milan–San Remo cycling race.
-
D.
numberOfVueltaAEspanaOverallVictories
Indicates the total count of times an entity has won the Vuelta a España general (overall) classification.
-
E.
GiroDItaliaOverallWinsYears
Indicates the specific years in which an entity achieved overall (general classification) victories in the Giro d'Italia.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:48 a.m.