Triple
T2065158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Support Unit |
E45881
|
entity |
| Predicate | lawEnforcementDomain |
P7908
|
FINISHED |
| Object | aerial law enforcement |
—
|
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: aerial law enforcement | Statement: [Air Support Unit, lawEnforcementDomain, aerial law enforcement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementDomain Context triple: [Air Support Unit, lawEnforcementDomain, aerial law enforcement]
-
A.
typeOfLawEnforcement
chosen
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
B.
enforcementAgency
Indicates that one entity serves as the authority responsible for enforcing laws, rules, or regulations related to another entity.
-
C.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
-
D.
lawEnforcementResponse
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
-
E.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
- 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_69a8891b38288190abd572ccad9b6928 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9d5147c8190a264fe42f0634cec |
completed | March 7, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69abb7aee9b48190999620176e3a6ee2 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:40 p.m.