Triple
T27524042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan–South Korea |
E694786
|
entity |
| Predicate | hasTradeIssue |
P114170
|
FINISHED |
| Object | export controls dispute |
—
|
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: export controls dispute | Statement: [Japan–South Korea, hasTradeIssue, export controls dispute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTradeIssue Context triple: [Japan–South Korea, hasTradeIssue, export controls dispute]
-
A.
hasIssueWith
chosen
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
hadIssue
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
C.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
-
D.
hasRecentIssue
Indicates that an entity is associated with an issue or problem that has occurred within a recent or specified time frame.
-
E.
hasTrade
Indicates a relationship where one entity engages in or maintains a commercial exchange or trading activity with another entity.
- 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_69ef538550208190aa9de8e2cb260d93 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 27, 2026, 1:22 p.m.