Triple
T11310005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kuni no miyatsuko |
E267811
|
entity |
| Predicate | governedTypeOfArea |
P21121
|
FINISHED |
| Object | rural regions |
—
|
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: rural regions | Statement: [kuni no miyatsuko, governedTypeOfArea, rural regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governedTypeOfArea Context triple: [kuni no miyatsuko, governedTypeOfArea, rural regions]
-
A.
governanceArea
Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
-
B.
governsTerritoryType
chosen
Indicates that an authority or governing body exercises official control or administration over a specified type of territory.
-
C.
localGovernmentAreaType
Indicates the specific classification or category of a local government area within an administrative or governmental hierarchy.
-
D.
governedFor
Indicates that one entity exercised governing authority or administrative control on behalf of, or in the interest of, another entity.
-
E.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.