Triple
T19944226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Korean economy |
E479380
|
entity |
| Predicate | reformCharacteristics |
P98268
|
FINISHED |
| Object | selective market-oriented experiments |
—
|
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: selective market-oriented experiments | Statement: [North Korean economy, reformCharacteristics, selective market-oriented experiments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reformCharacteristics Context triple: [North Korean economy, reformCharacteristics, selective market-oriented experiments]
-
A.
typeOfReforms
chosen
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
B.
reformsBy
Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
-
C.
associatedReforms
Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
-
D.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
E.
relatedReforms
Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a64b2788190a49c4ed40aa93b98 |
completed | April 20, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.