Triple

T7771648
Position Surface form Disambiguated ID Type / Status
Subject Mpanda E179086 entity
Predicate hasTransport P1298 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, hasTransport, Mpanda Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mpanda Airport
Context triple: [Mpanda, hasTransport, 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c7045ebae88190a04c8f972795e615 completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d6d65e308190924c05df5a0a4959 completed March 29, 2026, 7:37 a.m.
Created at: March 27, 2026, 4:11 p.m.