Triple

T10777237
Position Surface form Disambiguated ID Type / Status
Subject Asaba E254229 entity
Predicate hasAirport P105 FINISHED
Object Asaba International Airport E548928 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: Asaba International Airport | Statement: [Asaba, hasAirport, Asaba International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asaba International Airport
Context triple: [Asaba, hasAirport, Asaba International Airport]
  • A. Asaba International Airport chosen
    Asaba International Airport is a regional airport serving the city of Asaba and surrounding areas in Delta State, Nigeria, handling both domestic and limited international flights.
  • B. Beni Airport
    Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
  • C. Makokou Airport
    Makokou Airport is a small public airport serving the town of Makokou in northeastern Gabon, providing regional air connectivity.
  • D. Umroi Airport
    Umroi Airport is a domestic airport serving the city of Shillong and the surrounding region in the Indian state of Meghalaya.
  • E. Sado Airport
    Sado Airport is a regional airport serving Sado Island in Niigata Prefecture, Japan, providing domestic air connections to the mainland.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732c18c3c819089d49e3e4585049e completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69de238ff88881908676d38dca041cb4 completed April 14, 2026, 11:22 a.m.
Created at: April 8, 2026, 9:16 p.m.