Triple
T22785657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Japan |
E563957
|
entity |
| Predicate | succeededByRole |
P41229
|
FINISHED |
| Object | spouse of the next Prime Minister of Japan |
—
|
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: spouse of the next Prime Minister of Japan | Statement: [First Lady of Japan, succeededByRole, spouse of the next Prime Minister of Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: succeededByRole Context triple: [First Lady of Japan, succeededByRole, spouse of the next Prime Minister of Japan]
-
A.
successorRole
Indicates that one role or position directly follows and replaces another in a sequence or organizational structure.
-
B.
subsequentRole
Indicates that one role or position is held after, and in succession to, another role or position.
-
C.
successorInSomeRoles
Indicates that one entity has taken over or followed another entity in certain specified roles or positions.
-
D.
successorStateRole
Indicates that one role represents the state or position that directly follows and replaces another role in a sequence or process.
-
E.
successionRole
chosen
Indicates a role or position that one entity assumes as the successor to another in a sequence of holders or office-bearers.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c30b4dc8190a5e23f4ce7feb300 |
completed | April 29, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:29 p.m.