Triple

T11071751
Position Surface form Disambiguated ID Type / Status
Subject AirSWIFT E261761 entity
Predicate callsign P1565 FINISHED
Object AIRSWIFT E261761 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: AIRSWIFT | Statement: [AirSWIFT, callsign, AIRSWIFT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AIRSWIFT
Context triple: [AirSWIFT, callsign, AIRSWIFT]
  • A. AirSWIFT chosen
    AirSWIFT is a Philippine regional airline known for operating domestic flights that connect Manila to popular island destinations such as El Nido and other tourist hubs.
  • B. Equair
    Equair is an Ecuadorian airline that operated domestic passenger flights, notably serving routes from Guayaquil and Quito.
  • C. Consair
    Consair is an abbreviated name historically used for Consolidated Aircraft, a major American aerospace manufacturer known for producing military aircraft such as the B-24 Liberator during World War II.
  • D. Canair
    Canair was a Spanish regional airline that operated inter-island flights in the Canary Islands.
  • E. Aerograd
    Aerograd is a 1935 Soviet science fiction and propaganda film directed by Alexander Dovzhenko, set in a futuristic Far Eastern border town threatened by foreign and internal enemies.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7994bbb30819090410bd3d0fde33c completed April 9, 2026, 12:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8bfb0c88190be27f5ce09b02c8b completed April 18, 2026, 6:09 p.m.
Created at: April 8, 2026, 9:26 p.m.