Triple

T7492815
Position Surface form Disambiguated ID Type / Status
Subject Kaliua District E177047 entity
Predicate borderingRegion P17964 FINISHED
Object Kigoma Region E5115 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: Kigoma Region | Statement: [Kaliua District, borderingRegion, Kigoma Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kigoma Region
Context triple: [Kaliua District, borderingRegion, Kigoma Region]
  • A. Kigoma Region chosen
    Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
  • B. Rukwa Region
    Rukwa Region is an administrative region in southwestern Tanzania known for its location along Lake Rukwa and its largely rural, agricultural economy.
  • 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. Simiyu Region
    Simiyu Region is an administrative region in northern Tanzania known for its predominantly rural economy based on agriculture and livestock.
  • E. Kagera Region
    Kagera Region is a northwestern region of Tanzania bordering Lake Victoria and several East African countries, known for its diverse ethnic groups, agriculture, and historical significance.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5784c908190b701959daf082625 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8de96d58c819086c308396a4a304e completed March 29, 2026, 8:11 a.m.
Created at: March 27, 2026, 3:43 p.m.