Triple
T12367143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic white cedar forest |
E294901
|
entity |
| Predicate | hasCharacteristicVegetation |
P953
|
FINISHED |
| Object | evergreen coniferous trees |
—
|
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: evergreen coniferous trees | Statement: [Atlantic white cedar forest, hasCharacteristicVegetation, evergreen coniferous trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacteristicVegetation Context triple: [Atlantic white cedar forest, hasCharacteristicVegetation, evergreen coniferous trees]
-
A.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
B.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
C.
hasVegetationLayer
Indicates that an entity possesses a distinct layer or cover of vegetation as part of its structure or surface.
-
D.
hasBiodiversityFeature
Indicates that an entity possesses or is associated with a specific biodiversity-related characteristic, attribute, or element.
-
E.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.