Triple
T35431497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater New Orleans Expressway |
E1024071
|
entity |
| Predicate | hasPolicePatrol |
P80479
|
FINISHED |
| Object | Causeway Police |
—
|
NE NERFINISHED |
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: Causeway Police | Statement: [Greater New Orleans Expressway, hasPolicePatrol, Causeway Police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolicePatrol Context triple: [Greater New Orleans Expressway, hasPolicePatrol, Causeway Police]
-
A.
policePresence
chosen
Indicates that law enforcement officers are present at or monitoring a particular location, event, or situation.
-
B.
hasPoliceAI
Indicates that an entity is equipped with, governed by, or utilizes an artificial intelligence system specifically for policing or law-enforcement functions.
-
C.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
D.
patrolsWith
Indicates that two or more entities conduct a patrol together as a coordinated or joint activity.
-
E.
hasPoliceInstitution
Indicates that an entity is associated with, governed by, or served by a particular police institution or law enforcement body.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff56ef0a5c8190ae729d66a8cf7fc4 |
completed | May 9, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ff539859c481909ec56310da418688 |
completed | May 9, 2026, 3:32 p.m. |
Created at: May 3, 2026, 4:03 p.m.