Triple
T7313854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buk District, Busan |
E168159
|
entity |
| Predicate | hasSubdivisionNameLanguage |
P66955
|
FINISHED |
| Object | Korean |
—
|
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: Korean | Statement: [Buk District, Busan, hasSubdivisionNameLanguage, Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionNameLanguage Context triple: [Buk District, Busan, hasSubdivisionNameLanguage, Korean]
-
A.
subdivisionNameLanguage
chosen
Indicates the language in which the name of a subdivision (such as a region, district, or administrative unit) is expressed.
-
B.
subdivisionISONameLanguage
Indicates the language in which the ISO-standardized name of a geographic or administrative subdivision is expressed.
-
C.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
D.
hasSubdivisionCode
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
-
E.
hasSubdivisionStandard
Indicates that a governing standard or specification defines how an entity is to be subdivided into smaller parts or units.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ec03a7248190beb1dec612725e5b |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:02 p.m.