Triple

T10540919
Position Surface form Disambiguated ID Type / Status
Subject Đáy River E248691 entity
Predicate flowsThrough P225 FINISHED
Object Ứng Hòa district E50166 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: Ứng Hòa district | Statement: [Đáy River, flowsThrough, Ứng Hòa district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ứng Hòa district
Context triple: [Đáy River, flowsThrough, Ứng Hòa district]
  • A. Ứng Hòa District chosen
    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.
  • B. Phúc Thọ District
    Phúc Thọ District is a rural administrative district located on the outskirts of Hanoi, Vietnam.
  • C. Gia Lâm District
    Gia Lâm District is an administrative district on the eastern outskirts of Hanoi, Vietnam, known for its mix of rapidly urbanizing areas and traditional rural communities.
  • D. Hiệp Hòa District
    Hiệp Hòa District is a rural administrative district in Bắc Giang Province, Vietnam, known for its agricultural economy and proximity to the capital region.
  • E. 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.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a5918648190b16c2d1bc1bf015f completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f018324bf88190bcd2bf168b1065d3 completed April 28, 2026, 2:15 a.m.
Created at: April 6, 2026, 12:32 p.m.