Triple
T37505948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant (U.S. Navy) |
E932091
|
entity |
| Predicate | uniformUsage |
P2529
|
FINISHED |
| Object | insignia worn on service dress and working uniforms |
—
|
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: insignia worn on service dress and working uniforms | Statement: [Lieutenant (U.S. Navy), uniformUsage, insignia worn on service dress and working uniforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformUsage Context triple: [Lieutenant (U.S. Navy), uniformUsage, insignia worn on service dress and working uniforms]
-
A.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
C.
standardUse
Indicates that something is used in a typical, expected, or officially accepted manner for its intended purpose.
-
D.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
E.
uniformizes
Indicates making multiple entities or elements consistent, standardized, or uniform in form, appearance, or behavior.
- 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.