Triple

T12155479
Position Surface form Disambiguated ID Type / Status
Subject DNYO E289563 entity
Predicate identifies P310 FINISHED
Object Yola Airport E297029 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: Yola Airport | Statement: [DNYO, identifies, Yola Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yola Airport
Context triple: [DNYO, identifies, Yola Airport]
  • A. Yola Airport chosen
    Yola Airport is a regional airport serving the city of Yola in northeastern Nigeria, handling domestic flights and limited international traffic.
  • B. Ulei Airport
    Ulei Airport is a small regional airfield serving the island of Ambrym in Vanuatu, providing local and inter-island air connections.
  • C. Muanda Airport
    Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
  • D. Kalemie Airport
    Kalemie Airport is a public airport serving the town of Kalemie in the Tanganyika Province of the Democratic Republic of the Congo, providing regional air transport connections.
  • E. Umroi Airport
    Umroi Airport is a domestic airport serving the city of Shillong and the surrounding region in the Indian state of Meghalaya.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c1673c8190830cd15525d16869 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63ee46e608190ac824c3c8306013e completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:50 p.m.