Triple

T6826365
Position Surface form Disambiguated ID Type / Status
Subject Binter Canarias E157024 entity
Predicate hasSubsidiary P254 FINISHED
Object Naysa
Naysa is a regional Spanish airline that operates inter-island flights in the Canary Islands.
 E623359 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: Naysa | Statement: [Binter Canarias, hasSubsidiary, Naysa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Naysa
Context triple: [Binter Canarias, hasSubsidiary, Naysa]
  • A. Miriam Nicado García
    Miriam Nicado García is a Cuban mathematician and academic who became the first woman to serve as rector of the University of Havana.
  • B. Leona Maricle
    Leona Maricle was an American stage and film actress active in the early 20th century, known for her character roles in both Broadway productions and Hollywood movies.
  • C. Josie Trinidad
    Josie Trinidad is an American story artist and writer best known for her work on Disney animated films such as Zootopia and Ralph Breaks the Internet.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Gloria Akalitus
    Gloria Akalitus is a strict, bureaucratic hospital administrator and recurring character on the television series "Nurse Jackie."
  • 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: Naysa
Triple: [Binter Canarias, hasSubsidiary, Naysa]
Generated description
Naysa is a regional Spanish airline that operates inter-island flights in the Canary Islands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Naysa
Target entity description: Naysa is a regional Spanish airline that operates inter-island flights in the Canary Islands.
  • A. Miriam Nicado García
    Miriam Nicado García is a Cuban mathematician and academic who became the first woman to serve as rector of the University of Havana.
  • B. Leona Maricle
    Leona Maricle was an American stage and film actress active in the early 20th century, known for her character roles in both Broadway productions and Hollywood movies.
  • C. Josie Trinidad
    Josie Trinidad is an American story artist and writer best known for her work on Disney animated films such as Zootopia and Ralph Breaks the Internet.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Gloria Akalitus
    Gloria Akalitus is a strict, bureaucratic hospital administrator and recurring character on the television series "Nurse Jackie."
  • 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_69c72fa6fc80819081f012ea2207c25a completed March 28, 2026, 1:32 a.m.
NEDg Description generation batch_69c7313f9df08190b0184ade01037193 completed March 28, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_69c731a2d3fc81908fc90a9f9860311b completed March 28, 2026, 1:40 a.m.
Created at: March 27, 2026, 2:18 p.m.