Triple
T1282771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Squires |
E27363
|
entity |
| Predicate | jerseyNumberRetiredFor |
P559
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Virginia Squires, jerseyNumberRetiredFor, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyNumberRetiredFor Context triple: [Virginia Squires, jerseyNumberRetiredFor, none]
-
A.
leagueRetiredNumberBy
Indicates that a sports league has officially retired a specific jersey number in honor of a particular person or entity.
-
B.
dateOfJerseyRetirement
Indicates the date on which a team officially retired an athlete’s jersey number.
-
C.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
D.
retiredNumber
Indicates that an entity (typically a team or organization) has formally withdrawn a specific number from future use, usually to honor a particular individual or achievement associated with that number.
-
E.
retiredNumberHonoree
chosen
Indicates that an entity is honored by having its jersey or identification number formally retired by a team or organization.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b47be08190828a1c0a11d94ce8 |
completed | March 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.