Triple
T9562280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tây Đằng |
E230702
|
entity |
| Predicate | capitalOf |
P204
|
FINISHED |
| Object | Ba Vì District |
E45412
|
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: Ba Vì District | Statement: [Tây Đằng, capitalOf, Ba Vì District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ba Vì District Context triple: [Tây Đằng, capitalOf, Ba Vì District]
-
A.
Ba Vì District
chosen
Ba Vì District is a rural district on the western outskirts of Hanoi, Vietnam, known for its mountainous landscapes, Ba Vì National Park, and cultural sites.
-
B.
Long Bien District
Long Bien District is an urban district of Hanoi, Vietnam, known for its rapid development, residential complexes, and strategic location on the eastern bank of the Red River.
-
C.
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.
-
D.
Yên Lạc District
Yên Lạc District is a rural administrative district in Vĩnh Phúc Province in northern Vietnam.
-
E.
Do Son District
Do Son District is a coastal district of Hai Phong, Vietnam, known as a seaside resort area featuring popular beaches and tourism activities.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9965e7b881909df98e933db38092 |
completed | April 1, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deafff4b8c819099d47b48773c3629 |
completed | April 14, 2026, 9:22 p.m. |
Created at: March 30, 2026, 8:03 p.m.