Triple
T7667666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federico Higuaín |
E173663
|
entity |
| Predicate | shirtNumberAtColumbusCrew |
P2651
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Federico Higuaín, shirtNumberAtColumbusCrew, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shirtNumberAtColumbusCrew Context triple: [Federico Higuaín, shirtNumberAtColumbusCrew, 10]
-
A.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
shirtNumberTradition
Indicates a conventional or historically established assignment or significance of a particular shirt number within a team or sport.
-
C.
leaderJerseyColor
Indicates the color of the jersey worn by the current leader in a competition or ranking.
-
D.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
E.
shirtNumberInnovation
Indicates an association where an entity’s shirt number is linked to a novel or unconventional change, method, or feature related to numbering.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4 p.m.