Triple
T14187683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Hero military installation |
E351619
|
entity |
| Predicate | camouflageStyle |
P113134
|
FINISHED |
| Object | buildings disguised as civilian structures |
—
|
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: buildings disguised as civilian structures | Statement: [Camp Hero military installation, camouflageStyle, buildings disguised as civilian structures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: camouflageStyle Context triple: [Camp Hero military installation, camouflageStyle, buildings disguised as civilian structures]
-
A.
camouflagePattern
Indicates that one entity has a surface or visual design intended to conceal it by blending with its surroundings or disrupting its outline.
-
B.
camouflageEffectiveness
Indicates how well one entity’s appearance or behavior conceals it from detection by another entity or sensing system.
-
C.
canCamouflage
Indicates that an entity has the ability to blend into its surroundings or alter its appearance to avoid detection.
-
D.
camouflageSubstrate
Indicates that an entity uses another entity as the background or surface against which it is camouflaged.
-
E.
maskColor
Indicates the color attribute associated with a mask.
- F. None of above. chosen
Provenance (4 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61de509881908967ef5031f2a8d9 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:03 a.m.