Triple
T21509867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China–North Korea relations |
E530686
|
entity |
| Predicate | tensionFactor |
P144669
|
FINISHED |
| Object | North Korean nuclear tests |
—
|
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 nuclear tests | Statement: [China–North Korea relations, tensionFactor, North Korean nuclear tests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tensionFactor Context triple: [China–North Korea relations, tensionFactor, North Korean nuclear tests]
-
A.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
B.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
C.
tensionArea
Indicates the region or extent over which mechanical or emotional tension is distributed or experienced.
-
D.
hasTypeOfTension
Indicates that one entity is associated with, or characterized by, a specific kind or category of tension.
-
E.
tightens
Indicates that one entity makes another entity more secure, compact, or taut by applying constricting force or reducing looseness.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:25 p.m.