Triple
T35025677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Col de Marie-Blanque |
E1010329
|
entity |
| Predicate | firstFeaturedInTourDeFrance |
P158091
|
FINISHED |
| Object | 1978 |
—
|
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: 1978 | Statement: [Col de Marie-Blanque, firstFeaturedInTourDeFrance, 1978]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstFeaturedInTourDeFrance Context triple: [Col de Marie-Blanque, firstFeaturedInTourDeFrance, 1978]
-
A.
firstUsedInTourDeFrance
Indicates that something (such as equipment, technology, or a practice) was used for the first time during a specific edition of the Tour de France.
-
B.
firstTourDeFranceYear
Indicates the year in which an entity (typically a cyclist) first participated in the Tour de France.
-
C.
lastTourDeFranceParticipation
Indicates the most recent instance in which an entity took part in the Tour de France.
-
D.
firstTourDeFranceHeld
Indicates that the subject is the location or context in which the first Tour de France event was held.
-
E.
firstTourDeFranceInclusionYear
chosen
Indicates the year in which an entity (such as a cyclist, team, or nation) was first included or participated 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.