Triple
T36842062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenyan Drake |
E910432
|
entity |
| Predicate | wearsNumberForPosition |
P186573
|
FINISHED |
| Object | running back |
—
|
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: running back | Statement: [Kenyan Drake, wearsNumberForPosition, running back]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsNumberForPosition Context triple: [Kenyan Drake, wearsNumberForPosition, running back]
-
A.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
hasShirtNumberRole
Indicates that an entity holds a specific shirt number assignment or role, typically within a team or roster context.
-
C.
wearsNumberRetiredBy
Indicates that one entity wears a jersey number that has been officially retired in honor of another entity.
-
D.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
E.
jerseyNumberWornAtGame
Indicates the specific jersey number an entity wore during a particular game or match.
- F. None of above. chosen
Provenance (4 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_69f76e7f65a881908651b702da592b6d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.