Triple
T16233524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 圜丘坛 |
E394046
|
entity |
| Predicate | 建筑布局 |
P48747
|
FINISHED |
| Object | 中轴对称布局体系的一部分 |
—
|
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: 中轴对称布局体系的一部分 | Statement: [圜丘坛, 建筑布局, 中轴对称布局体系的一部分]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 建筑布局 Context triple: [圜丘坛, 建筑布局, 中轴对称布局体系的一部分]
-
A.
buildingStructure
Indicates that one entity is a structural component or physical part that forms, supports, or constitutes the construction of another entity.
-
B.
buildingShape
Indicates the geometric form or outline that characterizes a building’s overall structure.
-
C.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
D.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
E.
urbanLayout
chosen
Indicates how the spatial arrangement, organization, and structure of buildings, streets, and public spaces relate to one another within an urban area.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2be2f881908ec2483507cb0b00 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.