Triple
T24342889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 16 Blocks |
E613559
|
entity |
| Predicate | hasPoliceForceDepicted |
P81289
|
FINISHED |
| Object | New York City Police Department |
—
|
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: New York City Police Department | Statement: [16 Blocks, hasPoliceForceDepicted, New York City Police Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliceForceDepicted Context triple: [16 Blocks, hasPoliceForceDepicted, New York City Police Department]
-
A.
hasPoliceInstitution
Indicates that an entity is associated with, governed by, or served by a particular police institution or law enforcement body.
-
B.
hasOwnPoliceForce
Indicates that an entity maintains and controls its own dedicated police force or law enforcement agency.
-
C.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
D.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
E.
hasPoliceTheme
chosen
Indicates that something features police, law enforcement, or policing activities as a central theme or focus.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293260ffc81909dcfeab3e663d6ec |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:57 a.m.