Triple

T19359913
Position Surface form Disambiguated ID Type / Status
Subject Iringa Region E484249 entity
Predicate borders P224 FINISHED
Object Singida Region 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: Singida Region | Statement: [Iringa Region, borders, Singida Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Singida Region
Context triple: [Iringa Region, borders, Singida Region]
  • A. Singida Region chosen
    Singida Region is an administrative region in central Tanzania known for its semi-arid climate, agriculture, and role as a transport crossroads.
  • B. Simiyu Region
    Simiyu Region is an administrative region in northern Tanzania known for its predominantly rural economy based on agriculture and livestock.
  • C. Njombe Region
    Njombe Region is an administrative region in southern Tanzania known for its highland climate, agriculture (especially tea and timber), and proximity to the Southern Highlands.
  • D. Nyanza region
    Nyanza region is an area in western Kenya along Lake Victoria, known for its predominantly Luo population and the city of Kisumu as its main urban center.
  • E. Simanjiro District
    Simanjiro District is a largely rural, Maasai-inhabited administrative district in northern Tanzania known for its pastoralism, wildlife areas, and growing mining activities.
  • 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6190b343c81909734ba776fd196dc completed April 20, 2026, 12:16 p.m.
Created at: April 10, 2026, 1:34 p.m.