Triple
T22676770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tây Nguyên |
E560364
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Đà Lạt |
—
|
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: Đà Lạt | Statement: [Tây Nguyên, majorCity, Đà Lạt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Đà Lạt Context triple: [Tây Nguyên, majorCity, Đà Lạt]
-
A.
Đà Lạt
chosen
Đà Lạt is a temperate highland city in Vietnam known for its cool climate, pine forests, flower gardens, and French colonial architecture.
-
B.
Bảo Lộc
Bảo Lộc is a city in Vietnam’s Central Highlands known for its tea and coffee plantations and cool, misty climate.
-
C.
Buôn Ma Thuột
Buôn Ma Thuột is a major city in Vietnam renowned as the capital of the country’s coffee industry and the largest urban center in the Central Highlands region.
-
D.
Huế
Huế is a historic city in central Vietnam that served as the imperial capital of the Nguyễn Dynasty and is renowned for its ancient citadel, royal tombs, and rich cultural heritage.
-
E.
Phu Ly City
Phu Ly City is the capital and main urban, economic, and administrative center of Ha Nam Province in northern Vietnam.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785ca1e08190af1a6cdb51ca4fce |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 3:11 p.m.