Triple
T17477543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bình Định province |
E425577
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Quy Nhơn |
—
|
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: Quy Nhơn | Statement: [Bình Định province, capital, Quy Nhơn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quy Nhơn Context triple: [Bình Định province, capital, Quy Nhơn]
-
A.
Quy Nhơn
chosen
Quy Nhơn is a coastal city in central Vietnam known for its beaches, seafood, and growing role as a regional economic and tourism hub.
-
B.
Nha Trang
Nha Trang is a coastal resort city in Vietnam renowned for its sandy beaches, scuba diving, and vibrant tourism industry.
-
C.
Vung Tau
Vung Tau is a coastal city in southern Vietnam known as a major seaside resort and important maritime and oil industry hub.
-
D.
Bien Hoa
Bien Hoa is a major industrial city in southern Vietnam, located near Ho Chi Minh City and known for its large manufacturing zones and economic importance.
-
E.
Da Nang
Da Nang is a major coastal city in central Vietnam known for its sandy beaches, modern infrastructure, and proximity to historic sites like Hoi An and the Marble Mountains.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bd865081909b5f84405c40ff14 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.