Triple

T8585700
Position Surface form Disambiguated ID Type / Status
Subject Buganda E203300 entity
Predicate contains P35 FINISHED
Object Mukono E118761 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: Mukono | Statement: [Buganda, contains, Mukono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mukono
Context triple: [Buganda, contains, Mukono]
  • A. Mukono chosen
    Mukono is a town in central Uganda that serves as the administrative and commercial center of Mukono District, located just east of the capital Kampala.
  • B. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • C. Nyabira
    Nyabira is a small town in northern Zimbabwe located within Mashonaland West Province, serving as a local commercial and residential center.
  • D. Kalangoya
    Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • E. Masaka District
    Masaka District is an administrative district in southern Uganda known for its agricultural economy and its role as a key transport and commercial hub in the Central Region.
  • 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc457ab8b08190a53c730417288deb completed March 31, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebb9716948190b0eb61ddf25fb333 completed April 2, 2026, 6:55 p.m.
Created at: March 30, 2026, 6:22 p.m.