Triple
T19778485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A. C. Green |
E475068
|
entity |
| Predicate | wearsNumberMostNotably |
P2651
|
FINISHED |
| Object | 45 |
—
|
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: 45 | Statement: [A. C. Green, wearsNumberMostNotably, 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsNumberMostNotably Context triple: [A. C. Green, wearsNumberMostNotably, 45]
-
A.
wearsNumberRetiredBy
Indicates that one entity wears a jersey number that has been officially retired in honor of another entity.
-
B.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
D.
hasJerseyNumberRetired
Indicates that an entity has had its jersey number officially retired, typically in recognition of its contributions or achievements.
-
E.
wearsShoeSizeUS
Indicates that an entity wears shoes of a specified US shoe size.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65361a8e08190b52944aab25e45fa |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.