Triple
T2927677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stafford County Sheriff’s Office |
E78885
|
entity |
| Predicate | hasLawEnforcementRole |
P7908
|
FINISHED |
| Object | general policing |
—
|
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: general policing | Statement: [Stafford County Sheriff’s Office, hasLawEnforcementRole, general policing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawEnforcementRole Context triple: [Stafford County Sheriff’s Office, hasLawEnforcementRole, general policing]
-
A.
hasMilitaryAuthority
Indicates that one entity possesses formal power or command to direct, control, or make decisions over the military activities or forces of another entity.
-
B.
hasLegalRole
Indicates that an entity holds a specific legal capacity, status, or function in relation to another entity or context.
-
C.
typeOfLawEnforcement
chosen
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
D.
hasUnitedStatesMarshal
Indicates that an entity is associated with or served by a particular United States Marshal.
-
E.
hasCustodyRole
Indicates that one entity holds a specific custodial responsibility or role in relation to 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97ff0ddc8190acba9863bbe4f54b |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9606e8348190bb19df33a2709674 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:55 p.m.