Triple
T2594201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brittney Griner |
E58189
|
entity |
| Predicate | detentionYear |
P31117
|
FINISHED |
| Object | 2022 |
—
|
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: 2022 | Statement: [Brittney Griner, detentionYear, 2022]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detentionYear Context triple: [Brittney Griner, detentionYear, 2022]
-
A.
imprisonmentYear
chosen
Indicates the specific year in which an entity was imprisoned or placed into custody.
-
B.
durationOfImprisonment
Indicates the length of time that an entity is or was held in imprisonment.
-
C.
detainedFor
Indicates that one entity is being held in custody or confinement because of, or as a consequence of, another entity (such as a reason, charge, or event).
-
D.
imprisonedFor
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
E.
detainedUntil
Indicates that an entity is held in custody or confinement up to a specified time or until a particular condition is met.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd427f58c8190af1c1a9724158c96 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.