Triple
T53308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operational Camouflage Pattern |
E1049
|
entity |
| Predicate | patternType |
P1200
|
FINISHED |
| Object | digital-hybrid camouflage |
—
|
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: digital-hybrid camouflage | Statement: [Operational Camouflage Pattern, patternType, digital-hybrid camouflage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: patternType Context triple: [Operational Camouflage Pattern, patternType, digital-hybrid camouflage]
-
A.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
B.
camouflagePattern
chosen
Indicates that one entity has a surface or visual design intended to conceal it by blending with its surroundings or disrupting its outline.
-
C.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
D.
shape
Indicates that one entity has a particular geometric or physical form characterized by the other entity.
-
E.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24c709c248190bcd442c8d508e48c |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac3c8dc819099849023bdaa35a9 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.