Triple
T26344173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Sheriff’s Office |
E662731
|
entity |
| Predicate | usesBadgeTitle |
P103550
|
FINISHED |
| Object | Deputy Sheriff |
—
|
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: Deputy Sheriff | Statement: [New York City Sheriff’s Office, usesBadgeTitle, Deputy Sheriff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBadgeTitle Context triple: [New York City Sheriff’s Office, usesBadgeTitle, Deputy Sheriff]
-
A.
usesSameBadgeAs
Indicates that two entities use an identical badge, implying they share the same badge identifier or physical badge for access or identification purposes.
-
B.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
C.
usedTitleIn
Indicates that one entity employed or referenced another entity as a title in some context.
-
D.
badgeUsage
chosen
Indicates how and in what context a badge is applied, displayed, or utilized in relation to an entity or activity.
-
E.
usesTitleIn
Indicates that an entity is referred to using a particular title within a specified context or medium.
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 26, 2026, 10:41 p.m.