Triple
T23743436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Pickens |
E586747
|
entity |
| Predicate | hasJerseyNumberForPosition |
P141214
|
FINISHED |
| Object | 14 as wide receiver |
—
|
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: 14 as wide receiver | Statement: [George Pickens, hasJerseyNumberForPosition, 14 as wide receiver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJerseyNumberForPosition Context triple: [George Pickens, hasJerseyNumberForPosition, 14 as wide receiver]
-
A.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
jerseyNumberTeam
Indicates the association between a specific jersey number and the team for which that jersey number is used or assigned.
-
C.
hasShirtNumberRole
chosen
Indicates that an entity holds a specific shirt number assignment or role, typically within a team or roster context.
-
D.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
E.
hasJersey
Indicates that one entity possesses or is associated with a particular jersey.
- 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_69e24908efb08190bf755c3a9b91f222 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcbbcf988190b56d74af4b126bd8 |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:12 p.m.