Triple
T32652448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China–Vietnam relations |
E834770
|
entity |
| Predicate | ChinaRoleInVietnamTrade |
P174767
|
FINISHED |
| Object | largest trading partner of Vietnam |
—
|
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: largest trading partner of Vietnam | Statement: [China–Vietnam relations, ChinaRoleInVietnamTrade, largest trading partner of Vietnam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ChinaRoleInVietnamTrade Context triple: [China–Vietnam relations, ChinaRoleInVietnamTrade, largest trading partner of Vietnam]
-
A.
roleInVietnam
Indicates that an entity held a specific role, position, or function in the context of the Vietnam War or in Vietnam-related activities.
-
B.
VietnamEraRole
Indicates that an entity held a role, position, or status specifically during the Vietnam War era.
-
C.
ChinaRole
Indicates that an entity has a specific role, function, or position in relation to China.
-
D.
ChinaParticipation
Indicates that China takes part in, contributes to, or is involved in a specified event, activity, or arrangement.
-
E.
returnToVietnam
Indicates that an entity goes back to Vietnam after having been away.
- 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_69f3492f72248190ba42fa596aea50e1 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c7e32ec08190b74856937c4a9fc3 |
completed | May 3, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c77500a08190b2bdeca33bd2ac08 |
completed | May 3, 2026, 3:56 a.m. |
Created at: May 1, 2026, 1:08 a.m.