Triple

T18656691
Position Surface form Disambiguated ID Type / Status
Subject Mafinga Region E456082 entity
Predicate hasSettlement P1068 FINISHED
Object Mafinga Central NE NERFINISHED

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: Mafinga Central | Statement: [Mafinga Region, hasSettlement, Mafinga Central]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mafinga Central
Context triple: [Mafinga Region, hasSettlement, Mafinga Central]
  • A. Mafinga Central
    Mafinga Central is a mountainous region in northeastern Zambia that contains the country’s highest elevations within the Mafinga Hills.
  • B. Mafinga region chosen
    Mafinga Region is an administrative area in Tanzania that includes Mafinga Central and surrounding localities.
  • C. Mwanza Region
    Mwanza Region is an administrative region in northwestern Tanzania, located along the southern shores of Lake Victoria and known as a major economic and cultural center, including for the Sukuma people.
  • D. Nyanza region
    Nyanza region is an area in western Kenya along Lake Victoria, known for its predominantly Luo population and the city of Kisumu as its main urban center.
  • E. Vumba region
    The Vumba region is a scenic highland area in eastern Zimbabwe known for its lush forests, cool misty climate, and rich biodiversity, attracting nature lovers and tourists.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55084ca3481909ff3fd9045f25dcd completed April 19, 2026, 10 p.m.
Created at: April 10, 2026, 11:47 a.m.