Triple
T21927194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD Police Officer |
E541470
|
entity |
| Predicate | badgeWorn |
P4681
|
FINISHED |
| Object | NYPD shield |
—
|
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: NYPD shield | Statement: [NYPD Police Officer, badgeWorn, NYPD shield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: badgeWorn Context triple: [NYPD Police Officer, badgeWorn, NYPD shield]
-
A.
badge
chosen
Indicates that one entity confers, displays, or is associated with a symbolic mark or emblem representing status, achievement, role, or affiliation in relation to another entity.
-
B.
badgeVariesBy
Indicates that the characteristics or appearance of a badge change depending on some varying condition, context, or parameter.
-
C.
badgeUsage
Indicates how and in what context a badge is applied, displayed, or utilized in relation to an entity or activity.
-
D.
badgeMaterial
Indicates the material from which a badge is made.
-
E.
badgeText
Indicates that a visual badge or label is associated with an entity, displaying specific text content.
- 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123fc188481909c74fd5f1bd52258 |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:46 p.m.