Triple
T14830189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhongshan Park (Beijing) |
E348677
|
entity |
| Predicate | hasTypeOfGarden |
P12538
|
FINISHED |
| Object | Chinese classical garden |
—
|
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: Chinese classical garden | Statement: [Zhongshan Park (Beijing), hasTypeOfGarden, Chinese classical garden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGarden Context triple: [Zhongshan Park (Beijing), hasTypeOfGarden, Chinese classical garden]
-
A.
hasGardenType
chosen
Indicates that an entity possesses or is associated with a garden of a specified type.
-
B.
containsGarden
Indicates that one entity includes or has a garden within its area or boundaries.
-
C.
hasGardenSquare
Indicates that an entity includes, is adjacent to, or is otherwise associated with a garden square.
-
D.
hasGardenElement
Indicates that something includes, contains, or is associated with a specific element or feature within a garden.
-
E.
hasGardenRelation
Indicates a relationship in which one entity is associated with another through the presence, ownership, or inclusion of a garden.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded0748eec8190a39c94024c3a3e3e |
completed | April 14, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69de8c13418c819088ff9905ace1416a |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:51 a.m.