Triple

T6201634
Position Surface form Disambiguated ID Type / Status
Subject Chamber of Deputies of Rwanda E138646 entity
Predicate locatedIn P40 FINISHED
Object Kigali E87281 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: Kigali | Statement: [Chamber of Deputies of Rwanda, locatedIn, Kigali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kigali
Context triple: [Chamber of Deputies of Rwanda, locatedIn, Kigali]
  • A. Kigali chosen
    Kigali is the capital and largest city of Rwanda, known as a major political and economic hub in East Africa.
  • B. Gisenyi
    Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
  • C. Bukavu
    Bukavu is a major city in the eastern Democratic Republic of the Congo, located on the southwestern shore of Lake Kivu near the Rwandan border.
  • D. Gitega
    Gitega is the political and administrative capital city of Burundi, located in the central part of the country.
  • E. GOMA
    GOMA is a contemporary art museum known for showcasing modern and experimental artworks, often associated with major cultural institutions in cities like Brisbane and Glasgow.
  • 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_69c008acbea48190991c6b834bb45d65 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062559bcc81908942bb4d25fe8158 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d96415c8190b0c5c7f9fd19f5be completed March 24, 2026, 4:05 a.m.
Created at: March 22, 2026, 4:20 p.m.