Triple
T25772778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İlkay Gündoğan |
E649065
|
entity |
| Predicate | wearsNumberForClub |
P2651
|
FINISHED |
| Object | 22 at FC Barcelona |
—
|
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: 22 at FC Barcelona | Statement: [İlkay Gündoğan, wearsNumberForClub, 22 at FC Barcelona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsNumberForClub Context triple: [İlkay Gündoğan, wearsNumberForClub, 22 at FC Barcelona]
-
A.
clubNumberAtPSG
Indicates the specific jersey number a player wears or wore while playing for Paris Saint-Germain (PSG).
-
B.
wearsNumberRetiredBy
Indicates that one entity wears a jersey number that has been officially retired in honor of another entity.
-
C.
playsForNationalTeamShirtNumber
Indicates the shirt number a player wears when representing their national team in official matches.
-
D.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
E.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
- 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_69e7ab333b508190b6d708d8d9a328ed |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fe5a0ec0819085a2c7c652de294f |
completed | May 2, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 5:31 a.m.