Triple
T4974342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wardian |
E111728
|
entity |
| Predicate | hasLandscapingBy |
P19613
|
FINISHED |
| Object | landscape architects |
—
|
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: landscape architects | Statement: [The Wardian, hasLandscapingBy, landscape architects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapingBy Context triple: [The Wardian, hasLandscapingBy, landscape architects]
-
A.
hasLandscaping
Indicates that an entity possesses or is associated with designed outdoor grounds or landscape features.
-
B.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
-
C.
landscapeDesignedBy
chosen
Indicates that a particular landscape or outdoor environment was planned, created, or shaped by a specific designer or design entity.
-
D.
containsGarden
Indicates that one entity includes or has a garden within its area or boundaries.
-
E.
hasGardenSquare
Indicates that an entity includes, is adjacent to, or is otherwise associated with a garden square.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.