Triple

T5181963
Position Surface form Disambiguated ID Type / Status
Subject South Kivu E116941 entity
Predicate hasCity P316 FINISHED
Object Uvira E485479 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: Uvira | Statement: [South Kivu, hasCity, Uvira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uvira
Context triple: [South Kivu, hasCity, Uvira]
  • A. Uvira chosen
    Uvira is a city in the eastern Democratic Republic of the Congo, located on the northern shores of Lake Tanganyika near the border with Burundi.
  • B. Butembo
    Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
  • C. Butiama
    Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
  • D. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • E. Goma
    Goma is a city in eastern Democratic Republic of the Congo on the northern shore of Lake Kivu, known as a gateway to Virunga National Park and for its proximity to the active Nyiragongo volcano.
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd799bc58c819098a8e91e21baaef4 completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06ac60448190a2e97a4df03863ea completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:45 p.m.