Triple
T17319998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 内務大臣 |
E420533
|
entity |
| Predicate | oversawAgency |
P109273
|
FINISHED |
| Object | 警視庁（創設当初） |
—
|
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: 警視庁（創設当初） | Statement: [内務大臣, oversawAgency, 警視庁（創設当初）]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oversawAgency Context triple: [内務大臣, oversawAgency, 警視庁（創設当初）]
-
A.
headquartersOfImplementingAgency
Indicates that a specified location serves as the main headquarters of the agency responsible for implementing a particular project, program, or policy.
-
B.
regulatingAgency
Indicates that one entity serves as the official authority responsible for overseeing, controlling, or enforcing rules and standards on another entity or activity.
-
C.
mainImplementingAgency
chosen
Indicates which agency has primary responsibility for implementing a given project, program, or policy.
-
D.
oversawPolicy
Indicates that one entity had supervisory or managerial responsibility for the creation, implementation, or maintenance of a policy affecting another entity or domain.
-
E.
managingAgencyAbbreviation
Indicates that one entity is identified by the abbreviated name of the agency responsible for managing or overseeing it.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439a066b481908e8aee1885809eba |
completed | April 19, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.