Triple
T7540255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cam Ranh International Airport |
E178256
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Khanh Hoa Province |
E429666
|
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: Khanh Hoa Province | Statement: [Cam Ranh International Airport, locatedIn, Khanh Hoa Province]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khanh Hoa Province Context triple: [Cam Ranh International Airport, locatedIn, Khanh Hoa Province]
-
A.
Khánh Hòa province
chosen
Khánh Hòa province is a coastal region in south-central Vietnam known for its beaches, islands, and the resort city of Nha Trang.
-
B.
Binh Dinh Province
Binh Dinh Province is a coastal province in south-central Vietnam known for its historic Cham sites, martial arts traditions, and the city of Quy Nhon.
-
C.
Quang Duc Province
Quang Duc Province was a former administrative province of South Vietnam located in the Central Highlands region.
-
D.
Phú Yên province
Phú Yên province is a coastal region in south-central Vietnam known for its scenic beaches, rice fields, and relatively unspoiled natural landscapes.
-
E.
Da Nang Province
Da Nang Province is a coastal region in central Vietnam known for its beaches, modern cityscape, and role as a major economic and tourism hub.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f873b17081908bb70aea0010d072 |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8fa20137081909a21ac366c19407f |
completed | March 29, 2026, 10:08 a.m. |
Created at: March 27, 2026, 3:48 p.m.