Triple
T3176316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial Garden |
E66472
|
entity |
| Predicate | landscapeElement |
P45658
|
FINISHED |
| Object | evergreen 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 trees | Statement: [Imperial Garden, landscapeElement, evergreen trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landscapeElement Context triple: [Imperial Garden, landscapeElement, evergreen trees]
-
A.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
landscapeRole
Indicates the functional or symbolic role that an entity plays within a particular landscape or environmental setting.
-
C.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
D.
landscapeDesignedBy
Indicates that a particular landscape or outdoor environment was planned, created, or shaped by a specific designer or design entity.
-
E.
landscapeAbstraction
Indicates that one entity is an abstract or non-literal representation derived from the landscape or its features.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69b0bec8190957913b44d876079 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:06 p.m.