Triple
T26605008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Correctional Institution Coleman |
E667743
|
entity |
| Predicate | securityClassOf |
P51148
|
FINISHED |
| Object | FCI Coleman Low |
—
|
NE NERFINISHED |
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: FCI Coleman Low | Statement: [Federal Correctional Institution Coleman, securityClassOf, FCI Coleman Low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: securityClassOf Context triple: [Federal Correctional Institution Coleman, securityClassOf, FCI Coleman Low]
-
A.
hasSecurityClass
chosen
Indicates that an entity is assigned to or associated with a particular security classification level.
-
B.
securityClassification
Indicates the level or category of security sensitivity or access restriction assigned to an entity.
-
C.
securityLevelDetail
Indicates the specific classification or degree of security associated with an entity, often including nuanced or descriptive information about its protection level.
-
D.
securityClassStructure
Indicates a hierarchical or organizational relationship defining how security classifications are structured or arranged relative to one another.
-
E.
securityClassificationReason
Indicates the justification or basis for assigning a particular security classification to an entity or information.
- 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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 2:14 a.m.