Triple

T18073903
Position Surface form Disambiguated ID Type / Status
Subject Mengo E432504 entity
Predicate partOf P40 FINISHED
Object Kampala metropolitan area 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: Kampala metropolitan area | Statement: [Mengo, partOf, Kampala metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampala metropolitan area
Context triple: [Mengo, partOf, Kampala metropolitan area]
  • A. Kampala
    Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
  • B. Kampala District
    Kampala District is the central administrative and urban district of Uganda that encompasses the nation’s capital city, Kampala.
  • C. Entebbe
    Entebbe is a town in central Uganda on a peninsula into Lake Victoria, known for its international airport and the site of the 1976 hostage-rescue operation.
  • D. Greater Kampala Metropolitan Area chosen
    The Greater Kampala Metropolitan Area is the large urban and peri-urban region centered on Uganda’s capital, Kampala, encompassing surrounding rapidly growing towns and districts.
  • E. Lipa City
    Lipa City is a highly urbanized city in Batangas, Philippines, known as a commercial, educational, and religious center in the Calabarzon region.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ccefcdc4819086d0b224731bfc4d completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.