Triple
T6947445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zach Randolph |
E160831
|
entity |
| Predicate | jerseyNumberMostAssociated |
P2651
|
FINISHED |
| Object | 50 |
—
|
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: 50 | Statement: [Zach Randolph, jerseyNumberMostAssociated, 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyNumberMostAssociated Context triple: [Zach Randolph, jerseyNumberMostAssociated, 50]
-
A.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
teamMostAssociatedWith
Indicates the team with which an entity is most strongly or primarily associated, relative to other possible team affiliations.
-
C.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
D.
jerseyNumberManaged
Indicates that an entity is responsible for assigning, organizing, or overseeing jersey numbers for players or team members.
-
E.
leaderJerseyName
Indicates the name of the jersey worn by the current leader in a competition or ranking.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.