Triple
T11923903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpe d’Huez |
E283731
|
entity |
| Predicate | firstTourDeFranceFinishYear |
P102172
|
FINISHED |
| Object | 1952 |
—
|
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: 1952 | Statement: [Alpe d’Huez, firstTourDeFranceFinishYear, 1952]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstTourDeFranceFinishYear Context triple: [Alpe d’Huez, firstTourDeFranceFinishYear, 1952]
-
A.
firstTourDeFranceYear
Indicates the year in which an entity (typically a cyclist) first participated in the Tour de France.
-
B.
firstTourDeFranceHeld
Indicates that the subject is the location or context in which the first Tour de France event was held.
-
C.
firstTourYear
Indicates the year in which an entity (such as a performer, team, or event) undertook its first tour.
-
D.
TourDeFranceWins
Indicates the number of times an entity has won the Tour de France cycling race.
-
E.
TourDeFranceOverallWins
Indicates the number of times an entity has won the overall general classification of the Tour de France.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8e2fc648190a446c1917db1c7d9 |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.