Triple

T20131477
Position Surface form Disambiguated ID Type / Status
Subject Northern Tanzania E490904 entity
Predicate contains P35 FINISHED
Object Shinyanga 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: Shinyanga Region | Statement: [Northern Tanzania, contains, Shinyanga Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shinyanga Region
Context triple: [Northern Tanzania, contains, Shinyanga Region]
  • A. Shinyanga Region chosen
    Shinyanga Region is an administrative region in northwestern Tanzania known for its agriculture, mining activities, and proximity to Lake Victoria.
  • B. Nyanga Province
    Nyanga Province is a sparsely populated, resource-rich administrative region in southern Gabon known for its forests, rivers, and coastal areas along the Atlantic Ocean.
  • C. Rakai District
    Rakai District is a rural administrative district in southern Uganda known for its agricultural economy and its early prominence in the country’s HIV/AIDS epidemic.
  • D. Luweero District
    Luweero District is an administrative district in Uganda known for its role as a key battleground area during the Ugandan Bush War in the 1980s.
  • E. Mpigi District
    Mpigi District is an administrative district in central Uganda known for its agricultural activities and proximity to the capital, Kampala.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66762f0448190b7dbbc665e179ffc completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.