Triple
T10239080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 菅 義偉 |
E243540
|
entity |
| Predicate | 地方議員経験 |
P12544
|
FINISHED |
| Object | 横浜市会議員 |
—
|
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: 横浜市会議員 | Statement: [菅 義偉, 地方議員経験, 横浜市会議員]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地方議員経験 Context triple: [菅 義偉, 地方議員経験, 横浜市会議員]
-
A.
localGovernmentExperience
chosen
Indicates that an entity has held a role or performed duties within a local or municipal government context.
-
B.
governingExperience
Indicates that an entity has experience in governing or exercising authority over others or over an organization, territory, or system.
-
C.
stateLegislativeExperience
Indicates that an entity has previously served in, or held a position within, a state-level legislative body.
-
D.
heldPoliticalOfficeIn
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
E.
hasPoliticalOfficeScope
Indicates that a political office or position is limited to, defined within, or applicable to a specific jurisdiction, level, or scope of political authority.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:23 a.m.