Triple

T20325373
Position Surface form Disambiguated ID Type / Status
Subject Katanga Province E492318 entity
Predicate containsCity P294 FINISHED
Object Kolwezi 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: Kolwezi | Statement: [Katanga Province, containsCity, Kolwezi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kolwezi
Context triple: [Katanga Province, containsCity, Kolwezi]
  • A. Kolwezi chosen
    Kolwezi is a mining city in the southern Democratic Republic of the Congo, known for its rich copper and cobalt deposits and its role as a major industrial and economic center in the Lualaba province.
  • B. Nsukwa
    Nsukwa is a town in Aniocha South Local Government Area of Delta State, Nigeria, known as one of the traditional Igbo communities in the region.
  • C. Soroti
    Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
  • 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. 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.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778f20288190b1862d6be61bfb67 completed April 20, 2026, 6:59 p.m.
Created at: April 16, 2026, 11:21 a.m.