Triple
T30821034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coastal Douglas-fir zone |
E784919
|
entity |
| Predicate | hasAssociatedShrubSpecies |
P180545
|
FINISHED |
| Object | Oceanspray |
—
|
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: Oceanspray | Statement: [Coastal Douglas-fir zone, hasAssociatedShrubSpecies, Oceanspray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedShrubSpecies Context triple: [Coastal Douglas-fir zone, hasAssociatedShrubSpecies, Oceanspray]
-
A.
hasWeedySpecies
Indicates that an entity is associated with plant species considered weedy, invasive, or prone to unwanted spread.
-
B.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
C.
hasVegetationRole
Indicates that an entity participates in or is assigned a specific functional role related to vegetation (such as growth, maintenance, or impact on plant life).
-
D.
hasTrees
Indicates that something possesses or contains one or more trees.
-
E.
hasForestAssociation
Indicates an ecological or contextual relationship in which an entity is associated with, influenced by, or characteristically occurs in forest environments.
- 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 29, 2026, 8:44 p.m.