Triple
T435170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caryophyllales |
E9794
|
entity |
| Predicate | pigmentation |
P13150
|
FINISHED |
| Object | betalains mutually exclusive with anthocyanins |
—
|
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: betalains mutually exclusive with anthocyanins | Statement: [Caryophyllales, pigmentation, betalains mutually exclusive with anthocyanins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pigmentation Context triple: [Caryophyllales, pigmentation, betalains mutually exclusive with anthocyanins]
-
A.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
secondaryPigment
Indicates that one pigment functions as a secondary or supporting color relative to another primary pigment in a given context.
-
C.
primaryPigment
Indicates that one pigment is the main or dominant colorant used or present in relation to another entity.
-
D.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
E.
skinThickness
Indicates the measured thickness of an entity’s skin, typically quantifying how thick its outer tissue layer is.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ef0b6e0c8190ad6a335ee804829c |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2edda55e88190b7c17ba94d7df1ce |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.