Triple
T22440207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 仙洞御所（退位後） |
E554733
|
entity |
| Predicate | 文化的分類 |
P81632
|
FINISHED |
| Object | 日本の皇室建築 |
—
|
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: 日本の皇室建築 | Statement: [仙洞御所（退位後）, 文化的分類, 日本の皇室建築]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 文化的分類 Context triple: [仙洞御所（退位後）, 文化的分類, 日本の皇室建築]
-
A.
文化的評価
Indicates an assessment or judgment of something based on cultural values, norms, or standards.
-
B.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
C.
culturalType
chosen
Indicates the classification of something according to its cultural category, style, or tradition.
-
D.
culturalHeritageCategory
Indicates the classification of something according to its type or category within cultural heritage (e.g., monument, tradition, artifact).
-
E.
isCulturalDistinction
Indicates that one entity is recognized as a distinguishing cultural feature or marker in comparison to another entity 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae0edcc8190919b198035de0df2 |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.