Triple
T4621818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Treasures of Japan |
E101001
|
entity |
| Predicate | consequenceOfDesignation |
P7953
|
FINISHED |
| Object | strict regulations on alteration and export |
—
|
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: strict regulations on alteration and export | Statement: [National Treasures of Japan, consequenceOfDesignation, strict regulations on alteration and export]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfDesignation Context triple: [National Treasures of Japan, consequenceOfDesignation, strict regulations on alteration and export]
-
A.
effectOfDesignation
chosen
Indicates the causal impact or consequences that a particular designation or assigned status has on something.
-
B.
subsequentDesignation
Indicates that one designation or status follows and replaces another in a sequence or timeline.
-
C.
exampleDesignation
Indicates that one entity is identified or labeled as a representative or illustrative instance of another entity.
-
D.
religiousDesignation
Indicates the specific religious role, status, or affiliation assigned to an entity.
-
E.
cityPlanningDesignation
Indicates how an area is officially classified or designated within urban or municipal planning (e.g., residential, commercial, industrial).
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a0374308190aeaffc9d866a3742 |
completed | March 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.