Triple
T19129778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 郵政大臣 |
E468283
|
entity |
| Predicate | 制度的性格 |
P40450
|
FINISHED |
| Object | 旧日本政府の大臣ポスト |
—
|
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: 旧日本政府の大臣ポスト | Statement: [郵政大臣, 制度的性格, 旧日本政府の大臣ポスト]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 制度的性格 Context triple: [郵政大臣, 制度的性格, 旧日本政府の大臣ポスト]
-
A.
法的地位
Indicates the legal status or standing that an entity holds under a given legal system or framework.
-
B.
constitutionalRegime
Indicates that one entity functions as the constitutional system or framework of governance under which another entity is organized or operates.
-
C.
governingStyleAssociatedWith
chosen
Indicates a relationship where a particular governing style, method, or approach is linked or attributed to a specific entity (such as a leader, regime, or organization).
-
D.
legalSystematizationOf
Indicates the process or state in which laws, regulations, or legal principles are organized, codified, or structured into a coherent legal system or framework for something.
-
E.
typeOfPolity
Indicates that one entity is a political unit and the other specifies the kind or classification of that polity (e.g., empire, kingdom, republic).
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3cf8d348190b27fc7d7d39f46f1 |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.