Triple

T8368267
Position Surface form Disambiguated ID Type / Status
Subject Chương Mỹ District E197388 entity
Predicate borderedBy P224 FINISHED
Object Hà Đông District E214033 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: Hà Đông District | Statement: [Chương Mỹ District, borderedBy, Hà Đông District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hà Đông District
Context triple: [Chương Mỹ District, borderedBy, Hà Đông District]
  • A. Hà Đông District chosen
    Hà Đông District is an urban district of Hanoi, Vietnam, known for its rapid urbanization, traditional craft villages, and role as a key gateway area in the southwest of the capital.
  • B. Hoàng Mai District
    Hoàng Mai District is an urban district of Hanoi, Vietnam, known as one of the city’s most populous and rapidly developing residential and commercial areas.
  • C. Đan Phượng District
    Đan Phượng District is a rural administrative district located on the outskirts of Hanoi, Vietnam.
  • D. Ứng Hòa District
    Ứng Hòa District is a rural administrative district located in the southern part of Hanoi, Vietnam, known for its agricultural landscape and traditional craft villages.
  • E. Thanh Xuan District
    Thanh Xuan District is an urban district of Hanoi, Vietnam, known for its dense residential areas, universities, and growing commercial 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_69ca82f56730819080cec5d991c76f4c completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb808e56fc81908b5d37482f29452d completed March 31, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc7929e388190b35505378d0cf653 completed April 2, 2026, 1:34 a.m.
Created at: March 30, 2026, 6:01 p.m.