Triple

T1639221
Position Surface form Disambiguated ID Type / Status
Subject Katavi Region E35428 entity
Predicate partOf P40 FINISHED
Object Mainland Tanzania E175082 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: Mainland Tanzania | Statement: [Katavi Region, partOf, Mainland Tanzania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mainland Tanzania
Context triple: [Katavi Region, partOf, Mainland Tanzania]
  • A. mainland Tanzania chosen
    Mainland Tanzania is the continental portion of the United Republic of Tanzania, comprising its large landmass on the African mainland excluding the islands of Zanzibar.
  • B. Western Zone of Tanzania
    The Western Zone of Tanzania is an administrative area in western Tanzania that includes regions such as Kigoma along the shores of Lake Tanganyika.
  • C. Tanzania
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • D. Mwanza, Tanzania
    Mwanza is a major port city on the southern shores of Lake Victoria in northern Tanzania, known as an important commercial and transportation hub for the region.
  • E. Arusha, Tanzania
    Arusha, Tanzania is a major city in northern Tanzania known as a diplomatic hub and gateway to popular safari destinations and Mount Kilimanjaro.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a1c2b148190b6610237d5bede10 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58df433c81908d93515864c4bf09 completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.