Triple
T2786251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlanta U.S. Penitentiary |
E61817
|
entity |
| Predicate | adjacentFacilitySecurityClass |
P43566
|
FINISHED |
| Object | minimum security |
—
|
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: minimum security | Statement: [Atlanta U.S. Penitentiary, adjacentFacilitySecurityClass, minimum security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentFacilitySecurityClass Context triple: [Atlanta U.S. Penitentiary, adjacentFacilitySecurityClass, minimum security]
-
A.
adjacentToInfrastructure
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
B.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
C.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
-
D.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
isNamedFacilityOf
Indicates that a facility bears the official name associated with a particular entity (such as an organization, person, or place).
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 9:57 p.m.