Triple

T21665114
Position Surface form Disambiguated ID Type / Status
Subject Southern Malawi E534692 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Chikwawa 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: Chikwawa | Statement: [Southern Malawi, hasUrbanCenter, Chikwawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chikwawa
Context triple: [Southern Malawi, hasUrbanCenter, Chikwawa]
  • A. Chikwawa chosen
    Chikwawa is a town in southern Malawi known for its proximity to the Shire River and its role as an agricultural and trading center in the Lower Shire Valley.
  • B. Thyolo
    Thyolo is a town in southern Malawi known as an important center of the country’s tea-growing region.
  • C. Lilongwe
    Lilongwe is the largest city and administrative and political center of Malawi, located in the country’s central region.
  • D. Kapiri Mposhi
    Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
  • E. Zomba
    Zomba is a historic city in southern Malawi that served as the country’s former capital and remains an important administrative and educational center.
  • 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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c0b26c8819092c13e59dcc3c25c completed April 27, 2026, 2 p.m.
Created at: April 16, 2026, 6:36 p.m.