Triple
T22333446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA Basketball World Cup MVP 2019 |
E552080
|
entity |
| Predicate | winnerJerseyNumberAtTournament |
P86497
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [FIBA Basketball World Cup MVP 2019, winnerJerseyNumberAtTournament, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerJerseyNumberAtTournament Context triple: [FIBA Basketball World Cup MVP 2019, winnerJerseyNumberAtTournament, 9]
-
A.
playerOfTheTournament
Indicates that an entity has been recognized as the most outstanding performer in a particular tournament.
-
B.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
jerseyNumberWornAtGame
Indicates the specific jersey number an entity wore during a particular game or match.
-
D.
MVPJerseyNumber
chosen
Indicates the jersey number worn by the player who received the MVP (Most Valuable Player) award in a given context.
-
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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577cdcb08190a760e195c1051adb |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.