Triple
T18527386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otocolobus |
E452751
|
entity |
| Predicate | camouflageAdaptation |
P113134
|
FINISHED |
| Object | cryptic coloration |
—
|
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: cryptic coloration | Statement: [Otocolobus, camouflageAdaptation, cryptic coloration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: camouflageAdaptation Context triple: [Otocolobus, camouflageAdaptation, cryptic coloration]
-
A.
camouflageEffectiveness
Indicates how well one entity’s appearance or behavior conceals it from detection by another entity or sensing system.
-
B.
camouflageStyle
chosen
Indicates the type or pattern of camouflage used to visually conceal or disguise an entity in its environment.
-
C.
canCamouflage
Indicates that an entity has the ability to blend into its surroundings or alter its appearance to avoid detection.
-
D.
camouflagePattern
Indicates that one entity has a surface or visual design intended to conceal it by blending with its surroundings or disrupting its outline.
-
E.
camouflageSubstrate
Indicates that an entity uses another entity as the background or surface against which it is camouflaged.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533f9bd1081909743b24e290b7dfe |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.