Triple
T22833458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Văn Minh |
E565871
|
entity |
| Predicate | bearerNotablePosition |
P22252
|
FINISHED |
| Object | President of South 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: President of South Vietnam | Statement: [Văn Minh, bearerNotablePosition, President of South Vietnam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerNotablePosition Context triple: [Văn Minh, bearerNotablePosition, President of South Vietnam]
-
A.
bearerPosition
Indicates the spatial or positional relationship of a bearer (holder or carrier) relative to the item or entity it bears.
-
B.
notablePositionCombination
Indicates that an entity holds or has held a particularly significant combination of positions, roles, or offices considered notable when taken together.
-
C.
hasNotablePosition
chosen
Indicates that an entity holds or has held a position, role, or office considered notable or significant.
-
D.
notableHolderRole
Indicates that an entity is recognized for holding a particular role, office, or position in a notable or distinguished capacity.
-
E.
positionOfNotablePlayer
Indicates the role or playing position that a notable player occupies within a team or sport.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2d830881908d69929b854aad66 |
completed | April 29, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:35 p.m.