Triple
T19454841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawkins Police Department uniform |
E486708
|
entity |
| Predicate | portraysInstitutionType |
P2377
|
FINISHED |
| Object | small-town American police department |
—
|
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: small-town American police department | Statement: [Hawkins Police Department uniform, portraysInstitutionType, small-town American police department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysInstitutionType Context triple: [Hawkins Police Department uniform, portraysInstitutionType, small-town American police department]
-
A.
depictsInstitution
chosen
Indicates that one entity visually represents or portrays an institution as its subject.
-
B.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
governsInstitutionType
Indicates that an entity has authoritative control or regulatory oversight over a particular type or category of institution.
-
D.
involvesInstitution
Indicates that an action, event, or relationship includes or is associated with an institution as a participating party.
-
E.
coversInstitutionType
Indicates that one entity includes or applies to a particular type or category of institution.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c117ac8190a38c01c3191beaea |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.