Triple
T18871396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Execution of Sentences Courts |
E461575
|
entity |
| Predicate | enforcementDomain |
P131304
|
FINISHED |
| Object | custodial sentences |
—
|
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: custodial sentences | Statement: [Execution of Sentences Courts, enforcementDomain, custodial sentences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementDomain Context triple: [Execution of Sentences Courts, enforcementDomain, custodial sentences]
-
A.
regulatoryDomain
Indicates that one entity defines or governs the rules, policies, or constraints under which another entity must operate.
-
B.
enablesEnforcementOf
chosen
Indicates that one entity provides the authority, means, or conditions necessary for another entity to carry out enforcement actions or apply rules.
-
C.
enforcedOn
Indicates that a rule, policy, or constraint is applied with authority to a particular target or subject.
-
D.
enforcementStrength
Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
-
E.
enforcement
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a9dd04819083133ded30337962 |
completed | April 20, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69e48d22dde8819093b1d963bd673365 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.