Triple
T24690127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rip Hamilton |
E611411
|
entity |
| Predicate | primaryJerseyNumberWithPistons |
P104927
|
FINISHED |
| Object | 32 |
—
|
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: 32 | Statement: [Rip Hamilton, primaryJerseyNumberWithPistons, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryJerseyNumberWithPistons Context triple: [Rip Hamilton, primaryJerseyNumberWithPistons, 32]
-
A.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
jerseyNumberTeam
chosen
Indicates the association between a specific jersey number and the team for which that jersey number is used or assigned.
-
C.
playerWithNumber7
Indicates that an entity is a player who is associated with or wears the jersey number 7.
-
D.
jerseyNumberWornAtGame
Indicates the specific jersey number an entity wore during a particular game or match.
-
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_69e2c4d678b081908910f4271627a31a |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 3:20 a.m.