Triple
T30441692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 兵庫県宝塚市 |
E774460
|
entity |
| Predicate | 所属国会議員選挙区 |
P136654
|
FINISHED |
| Object | 兵庫県第6区 |
—
|
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: 兵庫県第6区 | Statement: [兵庫県宝塚市, 所属国会議員選挙区, 兵庫県第6区]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 所属国会議員選挙区 Context triple: [兵庫県宝塚市, 所属国会議員選挙区, 兵庫県第6区]
-
A.
representedElectoralDistrict
Indicates that an elected official served as the representative for a specific electoral district or constituency.
-
B.
legislativeDistrictOf
chosen
Indicates that a specified geographic or political area is the legislative district in which a given entity (such as a person, organization, or location) is situated or represented.
-
C.
electoralAreaOf
Indicates that a given electoral area (such as a district or ward) is the designated electoral division associated with a particular jurisdiction or entity.
-
D.
congressionalDistrict
Indicates that one entity is a congressional district that politically represents or geographically contains the other entity.
-
E.
senatorialDistrict
Indicates the specific senatorial district to which an entity (such as a person, place, or office) is assigned or associated.
- 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6869948e481908901dbda23952cc0 |
completed | May 2, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:08 p.m.