Triple

T8585886
Position Surface form Disambiguated ID Type / Status
Subject Gaddafi National Mosque E203304 entity
Predicate locatedOn P40 FINISHED
Object Old Kampala Hill E203306 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: Old Kampala Hill | Statement: [Gaddafi National Mosque, locatedOn, Old Kampala Hill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Old Kampala Hill
Context triple: [Gaddafi National Mosque, locatedOn, Old Kampala Hill]
  • A. Old Kampala Hill chosen
    Old Kampala Hill is a prominent historic hill in Uganda’s capital city, known as the original center of Kampala and home to notable landmarks such as the Uganda National Mosque.
  • B. Kibuli Hill
    Kibuli Hill is one of the prominent hills in Kampala, Uganda, known for its historic mosque and significant Muslim community institutions.
  • C. Rubaga Hill
    Rubaga Hill is one of Kampala’s prominent historic hills, known as the seat of the Rubaga Cathedral and a major center of the Catholic Church in Uganda.
  • D. Kololo Hill
    Kololo Hill is an upscale residential and diplomatic neighborhood in Kampala, Uganda, known for its embassies, luxury homes, and city views.
  • E. Nakasero Hill
    Nakasero Hill is an upscale, central neighborhood in Kampala known for hosting government offices, embassies, luxury hotels, and commercial centers.
  • 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_69cc457be9b88190bd9a2fc32350c31e completed March 31, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89c3421881908cfecba9a330b9c7 completed April 2, 2026, 3:22 p.m.
Created at: March 30, 2026, 6:22 p.m.