Triple

T11368608
Position Surface form Disambiguated ID Type / Status
Subject Siaya District E269280 entity
Predicate capital P234 FINISHED
Object Siaya E810862 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: Siaya | Statement: [Siaya District, capital, Siaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siaya
Context triple: [Siaya District, capital, Siaya]
  • A. Siaya chosen
    Siaya is a prominent town in western Kenya that serves as an administrative and commercial hub in the Nyanza region.
  • B. Sanyati
    Sanyati is a small town in Zimbabwe known for its agricultural activities and location within Mashonaland West Province.
  • C. Mangini
    Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
  • D. Kasangulu
    Kasangulu is a town and transport hub in western Democratic Republic of the Congo, located near Kinshasa and known for its position along key road and rail routes.
  • E. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea89e1148190b0ca29db9d7e2cbd completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58bdaabd48190ab533c1c7f3b5fd8 completed April 20, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:33 p.m.