Triple

T1524147
Position Surface form Disambiguated ID Type / Status
Subject Western Zone of Tanzania E32296 entity
Predicate hasRegionalCenter P1474 FINISHED
Object Tabora E33430 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: Tabora | Statement: [Western Zone of Tanzania, hasRegionalCenter, Tabora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tabora
Context triple: [Western Zone of Tanzania, hasRegionalCenter, Tabora]
  • A. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • B. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • C. Tabora Region chosen
    Tabora Region is an inland administrative region in western Tanzania known historically as a key hub for trade and rail transport.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • 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_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9080175588190bb3b1d4b17966f2f completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad370463ac8190b7740b4d16499725 completed March 8, 2026, 8:44 a.m.
Created at: March 4, 2026, 7:26 p.m.