Triple
T10256075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubashima |
E240468
|
entity |
| Predicate | hasEconomicZoneImplications |
P71487
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kubashima, hasEconomicZoneImplications, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicZoneImplications Context triple: [Kubashima, hasEconomicZoneImplications, yes]
-
A.
hasEconomicZoneImplication
chosen
Indicates that a relationship or action has consequences for the definition, use, rights, or regulations of an economic zone.
-
B.
hasEconomicZoneType
Indicates the specific classification or category of economic zone associated with an entity.
-
C.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
D.
countryExclusiveEconomicZone
Indicates that a specified maritime area lies within the exclusive economic zone legally designated to a particular country.
-
E.
hasMajorEconomicRegion
Indicates that an entity includes, is associated with, or is part of a primary or significant economic region within a larger economic or geographic context.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:30 a.m.