Triple
T18090623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Correctional Institution, Forrest City |
E432954
|
entity |
| Predicate | hasInmateGenderRestriction |
P15554
|
FINISHED |
| Object | male only |
—
|
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: male only | Statement: [Federal Correctional Institution, Forrest City, hasInmateGenderRestriction, male only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateGenderRestriction Context triple: [Federal Correctional Institution, Forrest City, hasInmateGenderRestriction, male only]
-
A.
hasInmateGender
Indicates that an inmate possesses a specified gender.
-
B.
hasGenderRequirement
chosen
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
C.
hasPerpetratorGender
Indicates that an action, event, or offense is associated with the specified gender of the perpetrator.
-
D.
hasPrisonerCategory
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
E.
hasPrisonerCondition
Indicates that a specified prisoner is subject to a particular condition, status, or restriction within a custodial or correctional context.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd17ba98819085a15e8593d98259 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.