Triple
T8325382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 岸信介 |
E194938
|
entity |
| Predicate | 前職_首相 |
P4358
|
FINISHED |
| Object | 石橋湛山 |
—
|
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: 石橋湛山 | Statement: [岸信介, 前職_首相, 石橋湛山]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 前職_首相 Context triple: [岸信介, 前職_首相, 石橋湛山]
-
A.
predecessorAsPrimeMinister
chosen
Indicates that one person previously held the office of Prime Minister immediately before another person.
-
B.
previousHeadOfStateTitle
Indicates that one entity is the official title or designation held by another entity in its role as a former head of state.
-
C.
predecessorInOffice
Indicates that one officeholder directly held a particular position before another officeholder in an official succession.
-
D.
precededInOfficeAsChancellorBy
Indicates that one individual assumed the role of Chancellor after another specific individual, who held the office immediately before them.
-
E.
incumbentPremierBeforeElection
Indicates that the referenced person was serving as premier immediately prior to the specified election.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f7fba688190b696593dfb2cde5d |
completed | March 31, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:56 p.m.