Triple
T14368080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Critérium du Dauphiné Libéré 1966 |
E356285
|
entity |
| Predicate | pelotonType |
P113757
|
FINISHED |
| Object | professional cyclists |
—
|
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: professional cyclists | Statement: [Critérium du Dauphiné Libéré 1966, pelotonType, professional cyclists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pelotonType Context triple: [Critérium du Dauphiné Libéré 1966, pelotonType, professional cyclists]
-
A.
bicycleType
Indicates the specific kind or category of bicycle associated with an entity.
-
B.
bikeType
Indicates the specific kind or category of bicycle associated with an entity.
-
C.
trekType
Indicates the specific category or style of trekking activity associated with an entity.
-
D.
cyclingCategory
Indicates the classification or type of cycling activity or discipline associated with an entity.
-
E.
rideType
Indicates the specific category or mode of transportation involved in a ride (e.g., standard, shared, premium).
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8faf00e8819087d7100e9d8c1877 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:15 a.m.