Triple
T17167637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaultheria |
E416646
|
entity |
| Predicate | foliageCharacteristic |
P126358
|
FINISHED |
| Object | aromatic |
—
|
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: aromatic | Statement: [Gaultheria, foliageCharacteristic, aromatic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foliageCharacteristic Context triple: [Gaultheria, foliageCharacteristic, aromatic]
-
A.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
B.
leafColor
Indicates the color or coloration characteristics of a leaf in relation to a plant or plant part.
-
C.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
D.
characteristicLeafTexture
Indicates the typical surface feel or texture that characterizes a leaf (e.g., smooth, rough, hairy) as a defining trait.
-
E.
leafNumberCharacteristic
Indicates a relationship where an entity is associated with a specific count or quantitative characteristic of its leaves.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f916833c81909c64e0d74b40a85b |
completed | April 18, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:37 a.m.