Triple
T10529709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 福田康夫 |
E248404
|
entity |
| Predicate | 議員種別 |
P22253
|
FINISHED |
| Object | 衆議院議員 |
—
|
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: 衆議院議員 | Statement: [福田康夫, 議員種別, 衆議院議員]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 議員種別 Context triple: [福田康夫, 議員種別, 衆議院議員]
-
A.
typeOfPolitician
chosen
Indicates that one politician belongs to a specific category or role of political office (e.g., senator, mayor, minister) within a political system.
-
B.
typeOfParliamentaryBody
Indicates the specific kind or classification of a parliamentary body that an entity represents (e.g., lower house, upper house, unicameral chamber).
-
C.
typeOfMinister
Indicates the specific governmental or religious office or role that a particular minister holds.
-
D.
constituencyType
Indicates the specific kind or category of electoral or representative district to which an entity belongs or refers.
-
E.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f7d8ac8190b90c1a7f77b23545 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:30 p.m.