Triple

T4347557
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Buganda E97941 entity
Predicate associatedWith P37 FINISHED
Object Kampala metropolitan area E40695 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: Kampala metropolitan area | Statement: [Kingdom of Buganda, associatedWith, Kampala metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampala metropolitan area
Context triple: [Kingdom of Buganda, associatedWith, Kampala metropolitan area]
  • A. Kampala chosen
    Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
  • B. 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.
  • C. Nairobi Metropolitan Region
    Nairobi Metropolitan Region is the expansive urban and economic area centered on Kenya’s capital, Nairobi, encompassing the city and its surrounding counties and towns.
  • D. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • E. Nairobi
    Nairobi is a fan-favorite character from the Spanish series "Money Heist," known for her sharp leadership, optimism, and expertise in overseeing the gang’s money-printing operations.
  • 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351a5559c819081608b0aaf6a0e66 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4fa3c388190a5e3ceb733e278f8 completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:15 p.m.