Triple
T30914454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denzel Dumfries |
E787539
|
entity |
| Predicate | shirtNumberNationalTeam |
P156847
|
FINISHED |
| Object | 22 |
—
|
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 | Statement: [Denzel Dumfries, shirtNumberNationalTeam, 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shirtNumberNationalTeam Context triple: [Denzel Dumfries, shirtNumberNationalTeam, 22]
-
A.
playsForNationalTeamShirtNumber
chosen
Indicates the shirt number a player wears when representing their national team in official matches.
-
B.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
hasShirtNumberRole
Indicates that an entity holds a specific shirt number assignment or role, typically within a team or roster context.
-
D.
shirtNumberType
Indicates the type or category of a shirt number assigned to an entity (for example, a player’s jersey number type).
-
E.
jerseyNumberTeam
Indicates the association between a specific jersey number and the team for which that jersey number is used or assigned.
- 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_69f224be300c8190a6513ce1ee0a7026 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69285fed48190b1eb55ff27eec20b |
completed | May 3, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:51 p.m.