Triple

T301501
Position Surface form Disambiguated ID Type / Status
Subject Governor-General of French Indochina E6205 entity
Predicate seat P75 FINISHED
Object Hanoi 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: Hanoi | Statement: [Governor-General of French Indochina, seat, Hanoi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanoi
Context triple: [Governor-General of French Indochina, seat, Hanoi]
  • 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. 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.
  • C. Hai Phong
    Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
  • D. 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.
  • 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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e9e6a8308190b9bd15310e324504 completed Feb. 28, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3bc2353408190b7658595498895bb completed March 1, 2026, 4:10 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.