Triple
T7673822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States–China relations |
E173810
|
entity |
| Predicate | sawTradeWarEscalation |
P78850
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [United States–China relations, sawTradeWarEscalation, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sawTradeWarEscalation Context triple: [United States–China relations, sawTradeWarEscalation, 2018]
-
A.
wasMilitarized
Indicates that an entity underwent a process of being organized, equipped, or adapted for military use or purposes.
-
B.
belligerentInterest
Indicates that an entity has a hostile, aggressive, or conflict-seeking attitude or stake toward another entity or situation.
-
C.
endedBilateralWarBetween
Indicates that an action or event brought a bilateral war between two parties to a conclusion or cessation.
-
D.
controlledTradeWith
Indicates a regulated or restricted trading relationship in which one entity manages, oversees, or limits the trade activities conducted with another entity.
-
E.
opposedWar
Indicates that an entity actively resisted, disagreed with, or worked against a particular war or military conflict.
- 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69c7048a01508190bc2e9ae8b863486c |
completed | March 27, 2026, 10:28 p.m. |
Created at: March 27, 2026, 4 p.m.