Triple

T6826366
Position Surface form Disambiguated ID Type / Status
Subject Binter Canarias E157024 entity
Predicate hasSubsidiary P254 FINISHED
Object Canair
Canair was a Spanish regional airline that operated inter-island flights in the Canary Islands.
 E621644 NE FINISHED

How this triple was built (4 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: Canair | Statement: [Binter Canarias, hasSubsidiary, Canair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Canair
Context triple: [Binter Canarias, hasSubsidiary, Canair]
  • A. Equair
    Equair is an Ecuadorian airline that operated domestic passenger flights, notably serving routes from Guayaquil and Quito.
  • B. Centrair
    Centrair is a major international airport serving Japan’s Chubu region, located on an artificial island in Ise Bay near Nagoya.
  • C. Esken Aviation
    Esken Aviation is the aviation-focused business segment of Esken Limited, involved in airport operations and related aviation services.
  • D. Skymaster
    Skymaster is the NATO reporting name for the Douglas C-54, a four-engine military transport aircraft widely used by the United States and its allies during and after World War II.
  • E. Northern Air
    Northern Air is a regional airline based in Fiji that operates domestic flights connecting smaller islands and remote communities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Canair
Triple: [Binter Canarias, hasSubsidiary, Canair]
Generated description
Canair was a Spanish regional airline that operated inter-island flights in the Canary Islands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Canair
Target entity description: Canair was a Spanish regional airline that operated inter-island flights in the Canary Islands.
  • A. Equair
    Equair is an Ecuadorian airline that operated domestic passenger flights, notably serving routes from Guayaquil and Quito.
  • B. Centrair
    Centrair is a major international airport serving Japan’s Chubu region, located on an artificial island in Ise Bay near Nagoya.
  • C. Esken Aviation
    Esken Aviation is the aviation-focused business segment of Esken Limited, involved in airport operations and related aviation services.
  • D. Skymaster
    Skymaster is the NATO reporting name for the Douglas C-54, a four-engine military transport aircraft widely used by the United States and its allies during and after World War II.
  • E. Northern Air
    Northern Air is a regional airline based in Fiji that operates domestic flights connecting smaller islands and remote communities.
  • F. None of above. chosen

Provenance (5 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d58375248190935dd38d618994e3 completed March 27, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723f12a148190adbb05782a2041b6 completed March 28, 2026, 12:42 a.m.
NEDg Description generation batch_69c7251ec97c819094fb2a73ac1d1d0e completed March 28, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_69c725d04d988190a4a6a1c73056cfd7 completed March 28, 2026, 12:50 a.m.
Created at: March 27, 2026, 2:18 p.m.