Triple
T6926637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cat Ba Island |
E160325
|
entity |
| Predicate | administrativeUnitOf |
P3892
|
FINISHED |
| Object | Cat Hai District |
E160324
|
NE 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: Cat Hai District | Statement: [Cat Ba Island, administrativeUnitOf, Cat Hai District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cat Hai District Context triple: [Cat Ba Island, administrativeUnitOf, Cat Hai District]
-
A.
Cat Hai District
chosen
Cat Hai District is a coastal island district of Hai Phong in northern Vietnam, known for encompassing part of the popular tourist destination Cat Ba Archipelago.
-
B.
Ky Son District
Ky Son District is a mountainous rural district in western Nghệ An Province, Vietnam, bordering Laos and known for its ethnic diversity and remote highland landscapes.
-
C.
Dien Chau District
Dien Chau District is an administrative rural district located within Nghe An Province in north-central Vietnam.
-
D.
Vu Ban District
Vu Ban District is a rural administrative district located within Nam Định Province in the Red River Delta region of northern Vietnam.
-
E.
Cau Giay District
Cau Giay District is an urban district of Hanoi, Vietnam, known for its rapid development, educational institutions, and growing commercial and residential areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1aa9c48190b63a04be2ed9e266 |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c769f6340c8190adab3e28cfe67e4a |
completed | March 28, 2026, 5:41 a.m. |
Created at: March 27, 2026, 2:27 p.m.