Triple
T14255229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China – Measures Affecting Imports of Automobile Parts |
E353367
|
entity |
| Predicate | officialWTODisputeNumber |
P47086
|
FINISHED |
| Object | DS339 |
—
|
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: DS339 | Statement: [China – Measures Affecting Imports of Automobile Parts, officialWTODisputeNumber, DS339]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialWTODisputeNumber Context triple: [China – Measures Affecting Imports of Automobile Parts, officialWTODisputeNumber, DS339]
-
A.
disputeNumber
chosen
Indicates the identifier or count associated with a specific dispute within a set of disputes.
-
B.
numberOfDisputations
Indicates the quantity of disputations (formal debates or arguments) associated with an entity.
-
C.
disputeInvolves
Indicates that a particular dispute includes or concerns the specified entities as participants or parties to the conflict.
-
D.
disputeSettlementNumber
Indicates the identifying number assigned to a specific dispute settlement case or process.
-
E.
disputeResolvedBy
Indicates that a particular dispute or conflict has been settled or resolved through the actions, decision, or intervention of a specified party or process.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62992a188190bc046fbab5a149d6 |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:09 a.m.