Triple

T9176493
Position Surface form Disambiguated ID Type / Status
Subject Gò Vấp District E220211 entity
Predicate nativeName P15 FINISHED
Object Quận Gò Vấp E220211 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: Quận Gò Vấp | Statement: [Gò Vấp District, nativeName, Quận Gò Vấp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quận Gò Vấp
Context triple: [Gò Vấp District, nativeName, Quận Gò Vấp]
  • A. Gò Vấp District chosen
    Gò Vấp District is a densely populated urban district in Ho Chi Minh City, Vietnam, known for its rapid development and proximity to Tan Son Nhat International Airport.
  • B. Tân Bình District
    Tân Bình District is an urban district of Ho Chi Minh City, Vietnam, best known as the location of the country’s busiest air gateway, Tan Son Nhat International Airport.
  • C. Tân Định Ward
    Tân Định Ward is a central urban ward of Ho Chi Minh City, Vietnam, known for its historic pink Tân Định Church and bustling traditional market.
  • D. Que Phong District
    Que Phong District is a rural mountainous district in northwestern Nghệ An Province, Vietnam, known for its ethnic diversity and forested landscapes.
  • E. Đống Đa District
    Đống Đa District is a central urban district of Hanoi, Vietnam, known for its dense population, historical sites, and role as a major commercial and educational hub of the capital.
  • 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_69ca83e589948190ac9907819db11ddf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa496548190a096969eebf732f3 completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d07771873c8190a9e2ebf2c83775be completed April 4, 2026, 2:29 a.m.
Created at: March 30, 2026, 7:23 p.m.