Triple

T7723986
Position Surface form Disambiguated ID Type / Status
Subject mainland Tanzania E175082 entity
Predicate hasRegion P285 FINISHED
Object Mbeya Region E183708 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: Mbeya Region | Statement: [mainland Tanzania, hasRegion, Mbeya Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mbeya Region
Context triple: [mainland Tanzania, hasRegion, Mbeya Region]
  • A. Mbeya Region chosen
    Mbeya Region is an administrative region in southwestern Tanzania known for its mountainous landscapes, agriculture, and role as a transport hub near the borders with Malawi and Zambia.
  • B. Ruvuma Region
    Ruvuma Region is a largely rural administrative area in southern Tanzania known for its wildlife, forests, and proximity to major conservation areas.
  • C. Iringa Region
    Iringa Region is an administrative area in south-central Tanzania known for its highland landscapes and as the gateway to Ruaha National Park, one of the country’s largest wildlife reserves.
  • D. Rukwa Region
    Rukwa Region is an administrative region in southwestern Tanzania known for its location along Lake Rukwa and its largely rural, agricultural economy.
  • E. Manzini Region
    Manzini Region is one of Eswatini’s four administrative regions, centrally located and home to the country’s largest urban and commercial center, Manzini city.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7031279708190a3a5fb64f9206974 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c97660dc8081908781da7ffd606f35 completed March 29, 2026, 6:58 p.m.
Created at: March 27, 2026, 4:05 p.m.