Triple
T35949056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FCI Butner Low |
E1039667
|
entity |
| Predicate | hasInmateCustodyType |
P105493
|
FINISHED |
| Object | low-security federal inmates |
—
|
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: low-security federal inmates | Statement: [FCI Butner Low, hasInmateCustodyType, low-security federal inmates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateCustodyType Context triple: [FCI Butner Low, hasInmateCustodyType, low-security federal inmates]
-
A.
hasInmateCustodyLevel
chosen
Indicates the security or supervision level at which an inmate is held in custody.
-
B.
detentionType
Indicates the specific category or form of detention applied to an entity within a custodial or restrictive context.
-
C.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
D.
hasInmateGender
Indicates that an inmate possesses a specified gender.
-
E.
detaineeStatus
Indicates the current legal or custodial condition of a person being detained, such as whether they are in custody, released, or under a specific detention regime.
- 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_69f76e25ea488190b7cee970b3e70382 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a008b8938608190adaccbd720111a18 |
completed | May 10, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_6a008b24baac8190baaaf50c2e9cc6bd |
completed | May 10, 2026, 1:41 p.m. |
Created at: May 3, 2026, 4:07 p.m.