Triple

T15933985
Position Surface form Disambiguated ID Type / Status
Subject Kalaw E386391 entity
Predicate governingCountryCapital P204 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: [Kalaw, governingCountryCapital, Naypyidaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naypyidaw
Context triple: [Kalaw, governingCountryCapital, 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. Nayapala
    Nayapala was a ruler of the Pala dynasty in eastern India, known for consolidating Pala power in Bengal and Bihar during the 11th century.
  • C. Nawalapitiya
    Nawalapitiya is a town in Sri Lanka known for its tea plantations and hilly terrain, located within the country's Central Province.
  • D. Natogyi
    Natogyi is a town located in central Myanmar’s Mandalay Region, known primarily as a local administrative and trading center for the surrounding rural area.
  • E. Napindan
    Napindan is a barangay (village-level administrative division) located in the city of Taguig in Metro Manila, Philippines.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a7bdd88190b1d7349ef920fd06 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0025ec39a8819081c0cf996bc59416 completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 4:53 a.m.