Triple

T217521
Position Surface form Disambiguated ID Type / Status
Subject Vietnam E4138 entity
Predicate hasCity P316 FINISHED
Object Hai Phong
Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
E28530 NE FINISHED

How this triple was built (4 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: Hai Phong | Statement: [Vietnam, hasCity, Hai Phong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hai Phong
Context triple: [Vietnam, hasCity, Hai Phong]
  • A. Hanoi
    Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
  • B. 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.
  • C. 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.
  • D. Tonkin
    Tonkin was a historical region in northern Vietnam, centered around Hanoi, that became a French protectorate and key part of colonial French Indochina.
  • E. Vina
    Vina is an alternate given name of Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hai Phong
Triple: [Vietnam, hasCity, Hai Phong]
Generated description
Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hai Phong
Target entity description: Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
  • A. Hanoi
    Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
  • B. 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.
  • C. 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.
  • D. Tonkin
    Tonkin was a historical region in northern Vietnam, centered around Hanoi, that became a French protectorate and key part of colonial French Indochina.
  • E. Vina
    Vina is an alternate given name of Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • F. None of above. chosen

Provenance (5 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c5062e48190833be10e4770e1e9 completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35274ba1c8190bc8d5ae975501d35 completed Feb. 28, 2026, 8:39 p.m.
NEDg Description generation batch_69a3531e3b108190af202a514b4d51da completed Feb. 28, 2026, 8:42 p.m.
NED2 Entity disambiguation (via description) batch_69a3536dbe5c8190ba47e03cf867c88a completed Feb. 28, 2026, 8:43 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.