Triple

T22872525
Position Surface form Disambiguated ID Type / Status
Subject Pleiku Airport E567235 entity
Predicate locatedIn P40 FINISHED
Object Pleiku NE NERFINISHED

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: Pleiku | Statement: [Pleiku Airport, locatedIn, Pleiku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pleiku
Context triple: [Pleiku Airport, locatedIn, Pleiku]
  • A. Pleiku chosen
    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.
  • B. Tuy Hoa
    Tuy Hoa is a coastal city in south-central Vietnam known for its beaches, rice fields, and role as the capital of Phú Yên Province.
  • C. Bien Hoa
    Bien Hoa is a major industrial city in southern Vietnam, located near Ho Chi Minh City and known for its large manufacturing zones and economic importance.
  • D. Pleiku Province
    Pleiku Province was a former province in Vietnam’s Central Highlands, historically significant as a major military area 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 (2 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_69e24589d8348190b96422d13a678bc1 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17f55c4b88190adb49871e496ca54 completed April 29, 2026, 3:47 a.m.
Created at: April 17, 2026, 3:38 p.m.