Triple

T14554048
Position Surface form Disambiguated ID Type / Status
Subject Mafinga Hills E341492 entity
Predicate contains P35 FINISHED
Object Mafinga Central E100432 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: Mafinga Central | Statement: [Mafinga Hills, contains, Mafinga Central]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mafinga Central
Context triple: [Mafinga Hills, contains, Mafinga Central]
  • A. Mafinga Central chosen
    Mafinga Central is a mountainous region in northeastern Zambia that contains the country’s highest elevations within the Mafinga Hills.
  • B. Mafinga region
    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 (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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f00cec8190a7b6482d18b9a216 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab9a5ac81908779a3c8701353fa completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.