Triple

T11786629
Position Surface form Disambiguated ID Type / Status
Subject Bình Xuyên District E280284 entity
Predicate hasProvinceCapital P3433 FINISHED
Object Vĩnh Yên E790346 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: Vĩnh Yên | Statement: [Bình Xuyên District, hasProvinceCapital, Vĩnh Yên]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vĩnh Yên
Context triple: [Bình Xuyên District, hasProvinceCapital, Vĩnh Yên]
  • A. Vĩnh Yên chosen
    Vĩnh Yên is an urban city in northern Vietnam that serves as an administrative, economic, and cultural hub within Vĩnh Phúc Province.
  • B. Hai Duong
    Hai Duong is a provincial city in northern Vietnam known as an important industrial and transportation hub between Hanoi and Hai Phong.
  • C. Ninh Binh City
    Ninh Binh City is an urban center in northern Vietnam known as the gateway to the scenic karst landscapes and cultural sites of the surrounding Ninh Binh Province.
  • D. Cao Lanh
    Cao Lanh is a city in Vietnam’s Mekong Delta region known as an administrative, commercial, and cultural hub of Dong Thap Province.
  • E. Hòa Lạc
    Hòa Lạc is a commune in the outskirts of Hanoi, Vietnam, known as a major hub for science, technology, and high-tech 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a586803481909af0032c35ca6e51 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090e8828481908baa7f6067190db3 completed April 28, 2026, 10:50 a.m.
Created at: April 8, 2026, 9:42 p.m.