Triple

T16418169
Position Surface form Disambiguated ID Type / Status
Subject Mara Region E398740 entity
Predicate borderRegion P12818 FINISHED
Object Arusha Region E258867 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: Arusha Region | Statement: [Mara Region, borderRegion, Arusha Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arusha Region
Context triple: [Mara Region, borderRegion, Arusha Region]
  • A. Arusha Region chosen
    Arusha Region is an administrative region in northern Tanzania known for its tourism hub city of Arusha and proximity to major national parks and Mount Kilimanjaro.
  • B. Dodoma Region
    Dodoma Region is an administrative region in central Tanzania that includes the national capital city, Dodoma.
  • 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. Dar es Salaam Region
    Dar es Salaam Region is a coastal administrative region in eastern Tanzania that encompasses the country’s largest city and main economic hub.
  • E. Kilimanjaro Region
    Kilimanjaro Region is an administrative area in northeastern Tanzania best known for encompassing Africa’s highest peak, Mount Kilimanjaro, and serving as a major hub for tourism and agriculture.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328798a488190a5fad01c3c95584c completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c6ca1bc8190a6c4f675ec8e3a53 completed May 10, 2026, 8:06 a.m.
Created at: April 10, 2026, 5:09 a.m.