Triple

T17619309
Position Surface form Disambiguated ID Type / Status
Subject Khánh Hòa province E429666 entity
Predicate hasCity P316 FINISHED
Object Cam Ranh 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: Cam Ranh | Statement: [Khánh Hòa province, hasCity, Cam Ranh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cam Ranh
Context triple: [Khánh Hòa province, hasCity, Cam Ranh]
  • A. Cam Ranh chosen
    Cam Ranh is a coastal city in Khánh Hòa Province, Vietnam, known for its deep-water bay and strategic military and transportation significance.
  • B. Chau Doc
    Chau Doc is a riverfront city in Vietnam’s An Giang Province, known as a cultural crossroads near the Cambodian border and a gateway to the Mekong Delta.
  • 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. Cam Ranh International Airport
    Cam Ranh International Airport is a major international airport in Vietnam serving the coastal resort city of Nha Trang and the surrounding Khanh Hoa Province.
  • E. Pleiku
    Pleiku is a city in Vietnam’s Central Highlands known as a regional hub for coffee production and as a strategic site during the Vietnam War.
  • 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d3547d88190ae3c9ffed63133c9 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.