Triple
T15632536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garland Greene |
E375850
|
entity |
| Predicate | settingOfIncarceration |
P6464
|
FINISHED |
| Object | federal prison |
—
|
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: federal prison | Statement: [Garland Greene, settingOfIncarceration, federal prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfIncarceration Context triple: [Garland Greene, settingOfIncarceration, federal prison]
-
A.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
B.
placeOfDetention
chosen
Indicates the location or facility where an entity is or was held in detention.
-
C.
usedForImprisoning
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
-
D.
isPenalInstitution
Indicates that an entity functions as a facility where individuals are legally confined as punishment or while awaiting legal proceedings.
-
E.
wasImprisonedIn
Indicates that an entity was held in confinement or incarcerated at a particular place or facility.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.