Triple
T15448993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2002 FIBA World Championship MVP |
E370097
|
entity |
| Predicate | winnerJerseyNumberAtTime |
P2651
|
FINISHED |
| Object | 41 |
—
|
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: 41 | Statement: [2002 FIBA World Championship MVP, winnerJerseyNumberAtTime, 41]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerJerseyNumberAtTime Context triple: [2002 FIBA World Championship MVP, winnerJerseyNumberAtTime, 41]
-
A.
hasJerseyNumberRetired
Indicates that an entity has had its jersey number officially retired, typically in recognition of its contributions or achievements.
-
B.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
retiredJerseyNumberByTeam
Indicates that a sports team has officially retired a specific jersey number in honor of a player or figure, making it unavailable for future use by team members.
-
D.
MVPJerseyNumber
Indicates the jersey number worn by the player who received the MVP (Most Valuable Player) award in a given context.
-
E.
jerseyNumberWornAtGame
Indicates the specific jersey number an entity wore during a particular game or match.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef9334c81908541e231b43eb012 |
completed | April 16, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.