Triple
T30441743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | アメリカ合衆国ミシガン州リボニア市 |
E774463
|
entity |
| Predicate | 州 |
P10261
|
FINISHED |
| Object | ミシガン州 |
—
|
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: ミシガン州 | Statement: [アメリカ合衆国ミシガン州リボニア市, 州, ミシガン州]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 州 Context triple: [アメリカ合衆国ミシガン州リボニア市, 州, ミシガン州]
-
A.
都道府県
Indicates a relationship where an entity is a Japanese prefecture or belongs to/pertains to a specific Japanese prefecture.
-
B.
stateOrTerritory
chosen
Indicates that one entity is a state or territory that is politically or administratively associated with another entity.
-
C.
stateOrRegion
Indicates that one entity is a state or region in which the other entity is located or with which it is associated.
-
D.
province
Indicates that one entity is an administrative subdivision or region (a province) governed by or belonging to another, typically larger, political or territorial entity.
-
E.
states
Indicates that an entity formally declares, expresses, or asserts a fact, opinion, or condition about another entity or situation.
- 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.