Triple
T4708635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Important Cultural Properties of Japan |
E104453
|
entity |
| Predicate | typicalExampleCategory |
P12230
|
FINISHED |
| Object | Buddhist temple buildings |
—
|
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: Buddhist temple buildings | Statement: [Important Cultural Properties of Japan, typicalExampleCategory, Buddhist temple buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalExampleCategory Context triple: [Important Cultural Properties of Japan, typicalExampleCategory, Buddhist temple buildings]
-
A.
typicalIn
chosen
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
C.
commonsCategory
Indicates that an entity is associated with a specific media or topic category on Wikimedia Commons.
-
D.
uniformCategory
Indicates that two or more entities share the same classification or type within a defined category system.
-
E.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd680beb508190b3d74e20e1c64405 |
completed | March 20, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69bd621ddcd88190903288566f5e5dab |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:17 p.m.