Triple
T30192815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honghe River |
E767539
|
entity |
| Predicate | languageName_Vietnamese |
P32764
|
FINISHED |
| Object | Sông Hồng |
—
|
NE NERFINISHED |
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: Sông Hồng | Statement: [Honghe River, languageName_Vietnamese, Sông Hồng]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageName_Vietnamese Context triple: [Honghe River, languageName_Vietnamese, Sông Hồng]
-
A.
VietnameseObjective
Indicates that an entity serves as the goal, target, or object of an action or intention specifically related to Vietnam or the Vietnamese language, culture, or context.
-
B.
nameInVietnamese
chosen
Indicates that one entity is the Vietnamese-language name or designation of another entity.
-
C.
hasVietnameseReading
Indicates that an entity is associated with a specific reading or pronunciation in the Vietnamese language.
-
D.
languageName
Indicates the specific name assigned to a language in the relationship.
-
E.
equivalentInVietnameseChuNom
Indicates that one entity is the equivalent representation of another entity in the Vietnamese Chữ Nôm writing system.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: April 29, 2026, 7:29 p.m.