Triple

T16363364
Position Surface form Disambiguated ID Type / Status
Subject BK Arena E397371 entity
Predicate locatedIn P40 FINISHED
Object Gasabo District E397368 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: Gasabo District | Statement: [BK Arena, locatedIn, Gasabo District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gasabo District
Context triple: [BK Arena, locatedIn, Gasabo District]
  • A. Gasabo District chosen
    Gasabo District is one of the three administrative districts of Kigali, Rwanda’s capital, encompassing both urban and peri-urban areas and hosting several key historical and governmental sites.
  • B. Mporokoso District
    Mporokoso District is an administrative district in northern Zambia known for its rural communities, waterfalls, and cultural diversity.
  • C. Goromonzi District
    Goromonzi District is an administrative district in northeastern Zimbabwe known for its agricultural activities and proximity to the capital, Harare.
  • D. Katete District
    Katete District is an administrative region in Zambia’s Eastern Province, known for its agricultural communities and its location along the key Great East Road corridor.
  • E. Kicukiro District
    Kicukiro District is an administrative district of Kigali, Rwanda, known for its rapidly growing urban areas, educational institutions, and key transport links.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff3aada88190a6e01f04c494a6ac completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00580fec0c8190b7fb73dbc637fb61 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:08 a.m.