Triple
T30832998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picket Fences |
E785273
|
entity |
| Predicate | hasLawEnforcementFocus |
P129507
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Picket Fences, hasLawEnforcementFocus, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawEnforcementFocus Context triple: [Picket Fences, hasLawEnforcementFocus, Yes]
-
A.
lawEnforcementFunction
Indicates that an entity performs, is responsible for, or is associated with official law enforcement duties or activities.
-
B.
lawEnforcementContext
chosen
Indicates that the relationship or action occurs within, is shaped by, or is relevant to a law enforcement setting, process, or activity.
-
C.
lawEnforcementLabel
Indicates that an entity has been designated, tagged, or classified by a law enforcement authority for monitoring, identification, or investigative purposes.
-
D.
shareLawEnforcement
Indicates that two entities collaborate or coordinate in law enforcement activities, resources, or responsibilities.
-
E.
isPartOfLawEnforcementSystem
Indicates that an entity belongs to, operates within, or functionally contributes to a law enforcement system or framework.
- 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: April 29, 2026, 8:44 p.m.