Triple

T7676623
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Health (Myanmar) E173875 entity
Predicate hasHeadquartersLocation P62 FINISHED
Object Naypyidaw E82022 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: Naypyidaw | Statement: [Ministry of Health (Myanmar), hasHeadquartersLocation, Naypyidaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naypyidaw
Context triple: [Ministry of Health (Myanmar), hasHeadquartersLocation, Naypyidaw]
  • A. Naypyidaw chosen
    Naypyidaw is Myanmar’s planned administrative city known for its vast, sparsely populated layout and role as the country’s political center.
  • B. Nawalapitiya
    Nawalapitiya is a town in Sri Lanka known for its tea plantations and hilly terrain, located within the country's Central Province.
  • C. Napindan
    Napindan is a barangay (village-level administrative division) located in the city of Taguig in Metro Manila, Philippines.
  • D. Nujaba
    Nujaba refers to a spiritual rank or class of saints in Islamic mysticism, regarded as righteous and divinely aided individuals of high but not supreme spiritual status.
  • E. Naju
    Naju is a historic city in South Korea known for its pear cultivation and location in the southwestern province of South Jeolla.
  • 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_69c6995703e0819081de77361b602e78 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701fbb4788190adf1e2d39be358c1 completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a240057081908826a5371ef5215b completed March 29, 2026, 3:53 a.m.
Created at: March 27, 2026, 4:01 p.m.