Triple
T6617041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cross-Strait relations |
E149577
|
entity |
| Predicate | tensionType |
P61198
|
FINISHED |
| Object | military tension |
—
|
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: military tension | Statement: [cross-Strait relations, tensionType, military tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tensionType Context triple: [cross-Strait relations, tensionType, military tension]
-
A.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
B.
hasTension
chosen
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
C.
strainType
Indicates the specific variety or subtype classification within a broader category of strains (e.g., biological, chemical, or product strains).
-
D.
tractionType
Indicates the type or method of traction applied or used in relation to an entity or system.
-
E.
tenderType
Indicates the method or form of payment or offer used in a transaction or exchange.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:58 p.m.