Triple

T19660507
Position Surface form Disambiguated ID Type / Status
Subject Phú Lộc District E472066 entity
Predicate borders P224 FINISHED
Object Đà Nẵng 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 Nẵng | Statement: [Phú Lộc District, borders, Đà Nẵng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Đà Nẵng
Context triple: [Phú Lộc District, borders, Đà Nẵng]
  • A. Da Nang chosen
    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.
  • B. Nha Trang
    Nha Trang is a coastal resort city in Vietnam renowned for its sandy beaches, scuba diving, and vibrant tourism industry.
  • C. 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.
  • D. Tuy Hoa
    Tuy Hoa is a coastal city in south-central Vietnam known for its beaches, rice fields, and role as the capital of Phú Yên Province.
  • E. Vung Tau
    Vung Tau is a coastal city in southern Vietnam known as a major seaside resort and important maritime and oil industry hub.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6414993ac8190b6da3702b1924b24 completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:45 p.m.