Triple

T2222747
Position Surface form Disambiguated ID Type / Status
Subject Đông Đô E48177 entity
Predicate hasSuccessorName P34641 FINISHED
Object Hà Nội E6204 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: Hà Nội | Statement: [Đông Đô, hasSuccessorName, Hà Nội]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hà Nội
Context triple: [Đông Đô, hasSuccessorName, Hà Nội]
  • A. Hanoi chosen
    Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
  • B. Hai Phong
    Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
  • C. Hanoi Capital Region
    The Hanoi Capital Region is a key metropolitan and administrative area in northern Vietnam centered on Hanoi, serving as the country’s political hub and a major economic and cultural center.
  • D. Saigon
    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.
  • E. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc5b262488190b6455d1d28d2306d completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69b367dc88ac81909e73e290c745b8be completed March 13, 2026, 1:26 a.m.
Created at: March 4, 2026, 7:47 p.m.