Triple

T20354390
Position Surface form Disambiguated ID Type / Status
Subject Southern Tanzania E496103 entity
Predicate contains P35 FINISHED
Object Katavi 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: Katavi Region | Statement: [Southern Tanzania, contains, Katavi Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katavi Region
Context triple: [Southern Tanzania, contains, Katavi Region]
  • A. Katavi Region chosen
    Katavi Region is a sparsely populated administrative region in western Tanzania known for its vast wilderness areas and the wildlife-rich Katavi National Park.
  • B. Serengeti District
    Serengeti District is an administrative district in northern Tanzania best known for encompassing a large portion of the world-famous Serengeti ecosystem and its wildlife.
  • C. Katavi National Park
    Katavi National Park is a remote wildlife reserve in western Tanzania known for its large concentrations of hippos, crocodiles, and buffalo, as well as its relatively untouched, off-the-beaten-path safari experience.
  • D. Singida Region
    Singida Region is an administrative region in central Tanzania known for its semi-arid climate, agriculture, and role as a transport crossroads.
  • E. Simiyu Region
    Simiyu Region is an administrative region in northern Tanzania known for its predominantly rural economy based on agriculture and livestock.
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67852ca9881908a5af18005639859 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:25 a.m.