Triple
T2032246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larix |
E44542
|
entity |
| Predicate | leafColorSeasonalChange |
P10587
|
FINISHED |
| Object | needles turn yellow in autumn |
—
|
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: needles turn yellow in autumn | Statement: [Larix, leafColorSeasonalChange, needles turn yellow in autumn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafColorSeasonalChange Context triple: [Larix, leafColorSeasonalChange, needles turn yellow in autumn]
-
A.
foliageSeasonalColor
chosen
Indicates the characteristic color that a plant’s foliage takes on during a particular season.
-
B.
leafColor
Indicates the color or coloration characteristics of a leaf in relation to a plant or plant part.
-
C.
treeColor
Indicates the color attribute associated with a tree.
-
D.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
E.
leafColorUpperSurface
Indicates the color exhibited on the upper surface of a leaf.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9313134819088133fb69b8f606f |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a8125881909c0cb58b777c1faa |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.