Triple

T7978281
Position Surface form Disambiguated ID Type / Status
Subject Mpanda District E185500 entity
Predicate hasTransportConnection P845 FINISHED
Object Mpanda Airport E183901 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: Mpanda Airport | Statement: [Mpanda District, hasTransportConnection, Mpanda Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mpanda Airport
Context triple: [Mpanda District, hasTransportConnection, Mpanda Airport]
  • A. Mpanda Airport chosen
    Mpanda Airport is a regional airport in western Tanzania that serves the town of Mpanda and the surrounding Katavi Region.
  • B. N’Dolo Airport
    N’Dolo Airport is a smaller, secondary airfield serving Kinshasa in the Democratic Republic of the Congo, primarily handling domestic and regional flights.
  • C. Kamuzu International Airport
    Kamuzu International Airport is the main international airport serving Lilongwe and one of the primary gateways to Malawi.
  • D. Matadi Tshimpi Airport
    Matadi Tshimpi Airport is a public airport serving the city of Matadi in the Kongo Central Province of the Democratic Republic of the Congo.
  • E. Sam Mbakwe International Cargo Airport
    Sam Mbakwe International Cargo Airport is the main airport serving Imo State in southeastern Nigeria, handling both passenger and cargo flights.
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bf84b1081908e60a556d984aad6 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0d3c724819087df03cea2ed998f completed March 31, 2026, 2:57 p.m.
Created at: March 30, 2026, 5:14 p.m.