Triple

T19856307
Position Surface form Disambiguated ID Type / Status
Subject Ruhuhu River E477140 entity
Predicate region P40 FINISHED
Object Njombe Region E1374643 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: Njombe Region | Statement: [Ruhuhu River, region, Njombe Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Njombe Region
Context triple: [Ruhuhu River, region, Njombe Region]
  • A. Njombe Region chosen
    Njombe Region is an administrative region in southern Tanzania known for its highland climate, agriculture (especially tea and timber), and proximity to the Southern Highlands.
  • 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. Singida Region
    Singida Region is an administrative region in central Tanzania known for its semi-arid climate, agriculture, and role as a transport crossroads.
  • D. Kigoma Region
    Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
  • E. Morogoro Region
    Morogoro Region is an administrative region in eastern Tanzania known for its diverse landscapes, agriculture, and proximity to major wildlife areas such as Mikumi National Park.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586c14fc81908d34785f1088b0a9 completed April 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0843d42838819087f89a9bf06a979b completed May 16, 2026, 10:15 a.m.
Created at: April 10, 2026, 1:51 p.m.