Triple
T5609770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Correctional Institution, Seagoville |
E147322
|
entity |
| Predicate | hasPrisonType |
P19110
|
FINISHED |
| Object | federal correctional institution |
—
|
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 correctional institution | Statement: [Federal Correctional Institution, Seagoville, hasPrisonType, federal correctional institution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrisonType Context triple: [Federal Correctional Institution, Seagoville, hasPrisonType, federal correctional institution]
-
A.
prisonType
chosen
Indicates the specific category or classification of a prison associated with an entity.
-
B.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
C.
hasPrisonerCategory
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
-
D.
hasPrisonService
Indicates that an entity provides, manages, or is responsible for prison-related services or operations for another entity.
-
E.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211dfc88819097b6d4254a61f65a |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.