Triple
T31155101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artemisia stelleriana |
E794180
|
entity |
| Predicate | foliageTexture |
P103575
|
FINISHED |
| Object | soft |
—
|
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: soft | Statement: [Artemisia stelleriana, foliageTexture, soft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foliageTexture Context triple: [Artemisia stelleriana, foliageTexture, soft]
-
A.
foliageCharacteristic
Indicates the specific traits or qualities of an entity’s foliage, such as its type, texture, color, or other distinguishing features.
-
B.
characteristicLeafTexture
chosen
Indicates the typical surface feel or texture that characterizes a leaf (e.g., smooth, rough, hairy) as a defining trait.
-
C.
inflorescenceTexture
Indicates the type or quality of surface feel or consistency characterizing an inflorescence.
-
D.
petalTexture
Indicates the type or quality of surface texture exhibited by a flower’s petals.
-
E.
leafColor
Indicates the color or coloration characteristics of a leaf in relation to a plant or plant part.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:06 p.m.