Triple
T8824714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alejandro Valverde |
E209985
|
entity |
| Predicate | riderType |
P84828
|
FINISHED |
| Object | all-rounder |
—
|
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: all-rounder | Statement: [Alejandro Valverde, riderType, all-rounder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riderType Context triple: [Alejandro Valverde, riderType, all-rounder]
-
A.
rideType
Indicates the specific category or mode of transportation involved in a ride (e.g., standard, shared, premium).
-
B.
notableRiderType
Indicates that an entity is notably associated with a particular type or category of rider (e.g., cyclist, jockey, driver).
-
C.
rideModel
Indicates that one entity is a specific model or type designation of a ride associated with another entity.
-
D.
bicycleType
Indicates the specific kind or category of bicycle associated with an entity.
-
E.
coachType
Indicates the specific category or role of a coach associated with an entity (e.g., head coach, assistant coach, position coach).
- 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc603220508190b64e22dec3ee5ceb |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cff3608819081d2d7e5c16d44b7 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:46 p.m.