Triple

T22629043
Position Surface form Disambiguated ID Type / Status
Subject Ê Đê E558499 entity
Predicate primaryLocation P3231 FINISHED
Object Khánh Hòa Province 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: Khánh Hòa Province | Statement: [Ê Đê, primaryLocation, Khánh Hòa Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khánh Hòa Province
Context triple: [Ê Đê, primaryLocation, Khánh Hòa 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. 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.
  • C. Ninh Thuận Province
    Ninh Thuận Province is a coastal province in south-central Vietnam known for its dry climate, Cham cultural heritage, and agriculture, particularly grape and sheep farming.
  • D. 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.
  • E. Phu Yen province
    Phu Yen province is a coastal province in south-central Vietnam known for its scenic beaches, lagoons, and relatively unspoiled natural landscapes.
  • 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_69e245467d9881908d6985bd0db7a1f1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f16e3febd081909ff21abef1e4035d completed April 29, 2026, 2:34 a.m.
Created at: April 17, 2026, 3:02 p.m.