Triple

T13836112
Position Surface form Disambiguated ID Type / Status
Subject SATA Air Açores E332530 entity
Predicate focusCity P164 FINISHED
Object Santa Maria Airport E389069 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: Santa Maria Airport | Statement: [SATA Air Açores, focusCity, Santa Maria Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Maria Airport
Context triple: [SATA Air Açores, focusCity, Santa Maria Airport]
  • A. Santa Maria Airport
    Santa Maria Airport is the main commercial airport serving the city of Aracaju in the Brazilian state of Sergipe.
  • B. Santa Maria Airport chosen
    Santa Maria Airport is the main air transport hub serving Santa Maria Island in Portugal’s Azores archipelago.
  • C. Santa Maria Public Airport
    Santa Maria Public Airport is a regional airport in California’s Central Coast region that serves the city of Santa Maria and surrounding communities with commercial, general aviation, and military operations.
  • D. Amerigo Vespucci Airport
    Amerigo Vespucci Airport is the main international airport serving Florence, Italy, handling domestic and European flights close to the city center.
  • E. Almirante Marcos A. Zar Airport
    Almirante Marcos A. Zar Airport is a public airport serving the city of Trelew in Chubut Province, Patagonia, Argentina.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de029b352081909605baaedc336213 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fba1ba309c81908d83ba7efc663787 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 10:13 p.m.