Triple
T9186118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guan Yu Temple (Jingzhou) |
E220462
|
entity |
| Predicate | hasCourtyardLayout |
P53931
|
FINISHED |
| Object | axial layout |
—
|
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: axial layout | Statement: [Guan Yu Temple (Jingzhou), hasCourtyardLayout, axial layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourtyardLayout Context triple: [Guan Yu Temple (Jingzhou), hasCourtyardLayout, axial layout]
-
A.
hasCourtyard
Indicates that one entity includes, features, or is characterized by the presence of a courtyard.
-
B.
hasCourtyardFeature
Indicates that a courtyard possesses or includes a specific feature or characteristic.
-
C.
hasCourtyardArea
Indicates that an entity includes or is associated with a courtyard and specifies the size or extent of that courtyard space.
-
D.
courtyardType
chosen
Indicates the specific kind or classification of a courtyard associated with an entity.
-
E.
courtyardShape
Indicates the geometric form or configuration that characterizes a courtyard.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31a52508190a83ccd76f3aa039b |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.