Triple
T21815247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Korean education system |
E538588
|
entity |
| Predicate | teacherEmployment |
P40561
|
FINISHED |
| Object | state-assigned |
—
|
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-assigned | Statement: [North Korean education system, teacherEmployment, state-assigned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teacherEmployment Context triple: [North Korean education system, teacherEmployment, state-assigned]
-
A.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
B.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
C.
educationalRoleSince
Indicates the point in time since which an entity has held a particular educational role or position in relation to another entity.
-
D.
hasTeacher
Indicates that one entity serves as an instructor or educator for another entity.
-
E.
hasTeachingStatus
chosen
Indicates that an entity holds a particular teaching-related role, capacity, or status in relation to another entity or 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_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.