Triple

T7177485
Position Surface form Disambiguated ID Type / Status
Subject Hai Hau District E167356 entity
Predicate administrativeCenter P1474 FINISHED
Object Yen Dinh E666209 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: Yen Dinh | Statement: [Hai Hau District, administrativeCenter, Yen Dinh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yen Dinh
Context triple: [Hai Hau District, administrativeCenter, Yen Dinh]
  • A. Yen Dinh chosen
    Yen Dinh is a township in Vietnam that serves as the administrative and economic center of Hai Hau District in Nam Dinh Province.
  • B. Ha Nam Province
    Ha Nam Province is a small, predominantly rural province in Vietnam’s Red River Delta region, known for its agriculture, traditional craft villages, and proximity to the capital city Hanoi.
  • C. Ninh Binh Province
    Ninh Binh Province is a northern Vietnamese province renowned for its karst landscapes, rice paddies, and river caves, including the UNESCO-listed Trang An Scenic Landscape Complex.
  • D. Hai Duong
    Hai Duong is a provincial city in northern Vietnam known as an important industrial and transportation hub between Hanoi and Hai Phong.
  • E. Ha Tinh Province
    Ha Tinh Province is a coastal province in north-central Vietnam known for its agricultural economy, historical sites, and vulnerability to severe weather and flooding.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e89022d48190a112c24df79ab62f completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c4097d88190b00a8c64ce6871e5 completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 2:49 p.m.