Triple
T33371993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 第1次安倍内閣 |
E854515
|
entity |
| Predicate | 農林水産大臣 |
P134220
|
FINISHED |
| Object | 松岡利勝 |
—
|
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: 松岡利勝 | Statement: [第1次安倍内閣, 農林水産大臣, 松岡利勝]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 農林水産大臣 Context triple: [第1次安倍内閣, 農林水産大臣, 松岡利勝]
-
A.
ministerOfEconomyTradeAndIndustry
Indicates that a person holds the official government position of Minister of Economy, Trade and Industry for a given jurisdiction.
-
B.
ministerIs
chosen
Indicates that one entity serves in the role or capacity of a minister in relation to another entity.
-
C.
deputyMinister
Indicates that one entity serves as the deputy minister (second-in-command or subordinate minister) to another entity within a governmental or ministerial hierarchy.
-
D.
ministerOfEducationCultureSportsScienceAndTechnology
Indicates that a person holds the official position of Minister responsible for education, culture, sports, science, and technology within a government.
-
E.
stateSecretary
Indicates that one entity holds or is associated with the position of state secretary in relation to another entity (such as a government, state, or administration).
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:35 a.m.