Triple
T21815239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Korean education system |
E538588
|
entity |
| Predicate | mediaInSchools |
P45097
|
FINISHED |
| Object | state-controlled |
—
|
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: state-controlled | Statement: [North Korean education system, mediaInSchools, state-controlled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaInSchools Context triple: [North Korean education system, mediaInSchools, state-controlled]
-
A.
mediumOfInstruction
Indicates that a particular language or medium is used as the primary means of instruction or teaching in an educational context.
-
B.
educationProxy
Indicates that one entity serves as a stand-in or representative for another entity in matters related to education or educational status.
-
C.
educationUse
chosen
Indicates the use or application of something specifically for educational purposes or in an educational context.
-
D.
educationIntegration
Indicates the incorporation or coordination of educational content, methods, or systems into a broader program, environment, or framework.
-
E.
hasStudentMedia
Indicates that an entity is associated with or provides media resources specifically created for or used by students.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc99bbc8190bf074930f361af7d |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.