Triple

T9438431
Position Surface form Disambiguated ID Type / Status
Subject Cầu Giấy Street E227577 entity
Predicate hasNameElement P3097 FINISHED
Object Cầu Giấy E40432 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: Cầu Giấy | Statement: [Cầu Giấy Street, hasNameElement, Cầu Giấy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cầu Giấy
Context triple: [Cầu Giấy Street, hasNameElement, Cầu Giấy]
  • A. Cầu Giấy District chosen
    Cầu Giấy District is an urban district of Hanoi, Vietnam, known for its rapid development, universities, and growing commercial and residential areas.
  • B. Minh Khai Ward
    Minh Khai Ward is an urban administrative subdivision of Hanoi, Vietnam, located within the central Hai Bà Trưng District.
  • C. Phú Thượng Ward
    Phú Thượng Ward is an urban administrative subdivision of Hanoi, Vietnam, located within the city’s Tây Hồ District.
  • D. Yên Phụ Ward
    Yên Phụ Ward is an urban administrative subdivision of Hanoi, Vietnam, situated along the West Lake and known for its historic village atmosphere and scenic lakeside setting.
  • E. Nghĩa Đô Ward
    Nghĩa Đô Ward is an urban administrative ward located within Hanoi, Vietnam, known as part of the Cầu Giấy District.
  • 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_69ca843884488190ad6cbe0153088234 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7ee1c8c48190a2ae8673eee07e9a completed April 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190cc06d48190b437edfc4fee8cce completed April 4, 2026, 10:29 p.m.
Created at: March 30, 2026, 7:50 p.m.