Triple
T16930732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qichun Garden |
E410699
|
entity |
| Predicate | hasDesignFeatures |
P1529
|
FINISHED |
| Object | traditional Chinese landscape design |
—
|
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: traditional Chinese landscape design | Statement: [Qichun Garden, hasDesignFeatures, traditional Chinese landscape design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignFeatures Context triple: [Qichun Garden, hasDesignFeatures, traditional Chinese landscape design]
-
A.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
designedFeature
Indicates that one entity is a feature or component intentionally planned, created, or specified by another entity as part of a design.
-
C.
hasDesignOption
Indicates that an entity is associated with or offers a particular design alternative or configurable design choice.
-
D.
testedDesignFeature
Indicates that a specific design feature has been subjected to a test or evaluation process.
-
E.
hasDesignConsideration
Indicates that one entity takes another entity into account as a factor, constraint, or requirement in its design or planning.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf248c6c81908fbf4d49e5381f08 |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.