Triple
T33692466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 香川1区 |
E863218
|
entity |
| Predicate | 輩出した政治家 |
P173201
|
FINISHED |
| Object | 大平正芳 |
—
|
NE NERFINISHED |
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: 大平正芳 | Statement: [香川1区, 輩出した政治家, 大平正芳]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 輩出した政治家 Context triple: [香川1区, 輩出した政治家, 大平正芳]
-
A.
notablePolitician
Indicates that the subject is a politician who is recognized as notable or significant in a political context.
-
B.
politicalActor
Indicates that an entity participates in political activities or holds a role within a political system or process.
-
C.
notableOfficeHolder
Indicates that an entity is a significant or distinguished holder of a particular office or position associated with another entity.
-
D.
wirdPolitischGetragenVon
Indicates that something (such as a measure, project, or position) is politically supported or backed by a specified actor or group.
-
E.
hasPoliticalFigure
chosen
Indicates a relationship where an entity is associated with or includes a specific political figure in a relevant role or context.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fa8450bc8190abb59e0bb53c9d68 |
completed | May 3, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.