Triple

T9550971
Position Surface form Disambiguated ID Type / Status
Subject An Giang E230419 entity
Predicate hasCity P316 FINISHED
Object Chau Doc E813693 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: Chau Doc | Statement: [An Giang, hasCity, Chau Doc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chau Doc
Context triple: [An Giang, hasCity, Chau Doc]
  • A. Chau Doc chosen
    Chau Doc is a riverfront city in Vietnam’s An Giang Province, known as a cultural crossroads near the Cambodian border and a gateway to the Mekong Delta.
  • B. Long Xuyen
    Long Xuyen is a major city in Vietnam’s Mekong Delta region, serving as the capital of An Giang Province and an important economic and cultural center.
  • C. 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.
  • D. 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.
  • E. Cam Ranh
    Cam Ranh is a coastal city in Khánh Hòa Province, Vietnam, known for its deep-water bay and strategic military and transportation significance.
  • 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_69ca847d3be8819099c9dad2a7e786f1 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd991df7308190a56d95f195627513 completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcaaeaa08190b90ca5600deb84a2 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 8:02 p.m.