Triple

T322775
Position Surface form Disambiguated ID Type / Status
Subject Saigon E6450 entity
Predicate shortName P43 FINISHED
Object HCMC E6450 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: HCMC | Statement: [Saigon, shortName, HCMC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HCMC
Context triple: [Saigon, shortName, HCMC]
  • A. Saigon chosen
    Saigon, now officially known as Ho Chi Minh City, is Vietnam’s largest city and a historic economic and cultural hub in the south of the country.
  • B. Hanoi
    Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
  • C. 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.
  • D. Hai Phong
    Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
  • E. Hoàn Kiếm District
    Hoàn Kiếm District is a central urban district of Hanoi, Vietnam, known for its historic Old Quarter, Hoàn Kiếm Lake, and role as the city’s commercial and cultural heart.
  • 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_69a2e7933d6c8190bb2592ad13286ef2 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea82ba748190bae651f5de908617 completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3cfe9c66c8190957b2ab7f5bae6fd completed March 1, 2026, 5:34 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.