Triple

T10529619
Position Surface form Disambiguated ID Type / Status
Subject North–South Railway E248402 entity
Predicate connectsCity P4245 FINISHED
Object Quy Nhon E425576 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: Quy Nhon | Statement: [North–South Railway, connectsCity, Quy Nhon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quy Nhon
Context triple: [North–South Railway, connectsCity, Quy Nhon]
  • A. Quy Nhơn chosen
    Quy Nhơn is a coastal city in central Vietnam known for its beaches, seafood, and growing role as a regional economic and tourism hub.
  • B. Da Nang
    Da Nang is a major coastal city in central Vietnam known for its sandy beaches, modern infrastructure, and proximity to historic sites like Hoi An and the Marble Mountains.
  • C. Nha Trang
    Nha Trang is a coastal resort city in Vietnam renowned for its sandy beaches, scuba diving, and vibrant tourism industry.
  • D. Pleiku
    Pleiku is a city in Vietnam’s Central Highlands known as a regional hub for coffee production and as a strategic site during the Vietnam War.
  • E. Lao Bảo
    Lao Bảo is a border town in Quảng Trị Province, Vietnam, known as a key commercial and transit point on the route between Vietnam and Laos.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509f7d8ac8190b90c1a7f77b23545 completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b1b0de8819089e39ec76e6bdf59 completed April 10, 2026, 7:10 p.m.
Created at: April 6, 2026, 12:30 p.m.