Triple

T16080405
Position Surface form Disambiguated ID Type / Status
Subject Galkayo E390093 entity
Predicate hasAirport P105 FINISHED
Object Galkayo Airport E390098 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: Galkayo Airport | Statement: [Galkayo, hasAirport, Galkayo Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Galkayo Airport
Context triple: [Galkayo, hasAirport, Galkayo Airport]
  • A. Galkayo Airport chosen
    Galkayo Airport is a regional public airport serving the city of Galkayo in central Somalia, facilitating domestic flights and connecting the Galmudug region with other parts of the country.
  • B. Bosaso Airport
    Bosaso Airport is the main civilian airport serving the coastal city of Bosaso in Somalia’s semi-autonomous Puntland region.
  • C. Kismayo Airport
    Kismayo Airport is the main civil and military airfield serving the port city of Kismayo in southern Somalia’s Jubaland region.
  • D. Hargeisa Airport
    Hargeisa Airport is the main civilian and former military airfield serving Hargeisa, the capital of Somaliland, in the Horn of Africa.
  • E. Berbera Airport
    Berbera Airport is a major airfield in Berbera, Somaliland, historically used as a strategic military and refueling base and now serving civilian air traffic for the region.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1844a5c68819086a13c93a787b436 completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe48adec081909623355eabee472c completed May 10, 2026, 1:51 a.m.
Created at: April 10, 2026, 4:57 a.m.