Triple

T14386120
Position Surface form Disambiguated ID Type / Status
Subject Panduranga E356727 entity
Predicate hasAlternativeName P39 FINISHED
Object Phan Rang E143595 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: Phan Rang | Statement: [Panduranga, hasAlternativeName, Phan Rang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phan Rang
Context triple: [Panduranga, hasAlternativeName, Phan Rang]
  • A. Phan Rang chosen
    Phan Rang is a coastal city in south-central Vietnam, known historically as a Cham cultural center and now as the capital of Ninh Thuận Province.
  • B. Cao Lanh
    Cao Lanh is a city in Vietnam’s Mekong Delta region known as an administrative, commercial, and cultural hub of Dong Thap Province.
  • C. Rach Gia
    Rach Gia is a coastal city in Vietnam’s Kien Giang Province, known as a gateway to the Gulf of Thailand and nearby islands such as Phu Quoc.
  • D. 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.
  • E. 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.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9025cff881908c08224d90d9f750 completed April 14, 2026, 7:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5513e8888190bc6b6cb33fd9b670 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:16 a.m.