Triple

T17309321
Position Surface form Disambiguated ID Type / Status
Subject Nome, Alaska E420249 entity
Predicate hasAirport P105 FINISHED
Object Nome Airport E1243251 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: Nome Airport | Statement: [Nome, Alaska, hasAirport, Nome Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nome Airport
Context triple: [Nome, Alaska, hasAirport, Nome Airport]
  • A. Nome Airport chosen
    Nome Airport is a public airport in Nome, Alaska, serving as a key regional hub for passenger and cargo flights in western Alaska.
  • B. Mitiga International Airport
    Mitiga International Airport is a major airport serving Tripoli, Libya, handling both domestic and international flights.
  • C. Homiel Airport
    Homiel Airport is a regional public airport serving the city of Gomel in southeastern Belarus, handling domestic and limited international flights.
  • D. Frans Sales Lega Airport
    Frans Sales Lega Airport is a regional airport serving the town of Ruteng on the island of Flores in East Nusa Tenggara, Indonesia.
  • E. Corvo Airport
    Corvo Airport is a small regional airport serving the remote island of Corvo in Portugal’s Azores archipelago.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439970cf08190bc9e49ba830da0d9 completed April 19, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e30934819087b7c838c8874aff completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:43 a.m.