Triple
T21509850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China–North Korea relations |
E530686
|
entity |
| Predicate | tradeDependence |
P23353
|
FINISHED |
| Object | North Korea heavily dependent on China |
—
|
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 Korea heavily dependent on China | Statement: [China–North Korea relations, tradeDependence, North Korea heavily dependent on China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tradeDependence Context triple: [China–North Korea relations, tradeDependence, North Korea heavily dependent on China]
-
A.
tradeAspect
Indicates a relationship where one entity is associated with a specific aspect, feature, or dimension of a trade or commercial transaction.
-
B.
tradeNetwork
chosen
Indicates a relationship where entities are connected through the exchange of goods, services, or resources within an ongoing system of trade.
-
C.
tradeDestination
Indicates the location or entity to which goods, services, or financial assets are sent or directed as part of a trade transaction.
-
D.
tradesAs
Indicates that one entity conducts business or is publicly known under the trading name or brand of another entity.
-
E.
tradeFocus
Indicates a primary emphasis on or specialization in a particular type of trade, transaction, or commercial activity within the relationship 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.