Triple
T6248191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanja |
E139773
|
entity |
| Predicate | notOfficiallyUsedIn |
P13196
|
FINISHED |
| Object | North Korean public writing |
—
|
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: North Korean public writing | Statement: [Hanja, notOfficiallyUsedIn, North Korean public writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notOfficiallyUsedIn Context triple: [Hanja, notOfficiallyUsedIn, North Korean public writing]
-
A.
notOfficialNameOf
Indicates that a given name or label is used for an entity but is not its official or formally recognized name.
-
B.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
C.
notOfficialLanguageOf
chosen
Indicates that a language is explicitly not recognized or designated as an official language of a given entity (such as a country, region, or organization).
-
D.
notOfficialCodeOf
Indicates that one entity is not the formally recognized or authorized code designation for the other entity.
-
E.
notUsedInCountry
Indicates that a given item, resource, or entity is not utilized, applied, or in operation within a specified country.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633a9a048190856d5247d3b28a2e |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:23 p.m.