Triple

T18073900
Position Surface form Disambiguated ID Type / Status
Subject Mengo E432504 entity
Predicate locatedIn P40 FINISHED
Object Kampala 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 | Statement: [Mengo, locatedIn, Kampala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampala
Context triple: [Mengo, locatedIn, Kampala]
  • 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. Mbarara
    Mbarara is a major city in southwestern Uganda that serves as a key commercial and transport hub for the region.
  • D. Nalubaale
    Nalubaale is the traditional Luganda name for Lake Victoria, one of Africa’s Great Lakes and the world’s largest tropical lake.
  • E. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central 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.