Triple
T21375928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julio Yarnel Rodríguez |
E527202
|
entity |
| Predicate | hasSportNumberType |
P93077
|
FINISHED |
| Object | uniform number |
—
|
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: uniform number | Statement: [Julio Yarnel Rodríguez, hasSportNumberType, uniform number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSportNumberType Context triple: [Julio Yarnel Rodríguez, hasSportNumberType, uniform number]
-
A.
sportNumber
Indicates the specific jersey or uniform number associated with an athlete in a sporting context.
-
B.
hasShirtNumberRole
Indicates that an entity holds a specific shirt number assignment or role, typically within a team or roster context.
-
C.
shirtNumberType
chosen
Indicates the type or category of a shirt number assigned to an entity (for example, a player’s jersey number type).
-
D.
numberOfSports
Indicates the quantity of distinct sports associated with or involved in a given entity.
-
E.
isInSportSystemOf
Indicates that one entity belongs to, is organized within, or operates under the structure of a particular sport system or sports organizational framework of another entity.
- 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5bb031988190ae587730a2131a50 |
completed | April 26, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:11 p.m.