Triple
T16919019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 佛香阁 |
E410393
|
entity |
| Predicate | 建筑特色 |
P6684
|
FINISHED |
| Object | 多重檐歇山顶与八角阁楼结合 |
—
|
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: 多重檐歇山顶与八角阁楼结合 | Statement: [佛香阁, 建筑特色, 多重檐歇山顶与八角阁楼结合]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 建筑特色 Context triple: [佛香阁, 建筑特色, 多重檐歇山顶与八角阁楼结合]
-
A.
architecturalDiversity
Indicates the degree to which a set of entities exhibits a variety of architectural styles, forms, or structural designs.
-
B.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
-
C.
architecturalFocus
Indicates that something is the primary subject, theme, or area of emphasis within the domain of architecture.
-
D.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
E.
architectFeatured
Indicates that an architect is prominently highlighted or showcased in relation to a particular work, project, or context.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdec3d0c8190994a0fca335c65d6 |
completed | April 18, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.