Triple

T6964449
Position Surface form Disambiguated ID Type / Status
Subject AJet E161451 entity
Predicate callsign P1565 FINISHED
Object CINAR
CINAR is the designated radio callsign used by the airline AJet for air traffic control and communication purposes.
E630624 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: CINAR | Statement: [AJet, callsign, CINAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CINAR
Context triple: [AJet, callsign, CINAR]
  • A. CINE
    CINE is the London Stock Exchange ticker symbol for Cineworld Group, one of the world’s largest cinema chains.
  • B. Cinemastar
    Cinemastar is a line of hard disk drives produced by HGST, typically designed for consumer and multimedia applications.
  • C. Vides Cinematografica
    Vides Cinematografica was an Italian film production company active in the mid-20th century, known for producing notable Italian and international cinema.
  • D. Cinema International Corporation
    Cinema International Corporation was a major international film distribution company formed by the joint venture of major Hollywood studios to handle the overseas release of their movies in the 1970s and early 1980s.
  • E. Yara Cinema
    Yara Cinema is a prominent and historic movie theater in Havana, Cuba, known as a cultural landmark and popular gathering place in the Vedado district.
  • 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: CINAR
Triple: [AJet, callsign, CINAR]
Generated description
CINAR is the designated radio callsign used by the airline AJet for air traffic control and communication purposes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CINAR
Target entity description: CINAR is the designated radio callsign used by the airline AJet for air traffic control and communication purposes.
  • A. CINE
    CINE is the London Stock Exchange ticker symbol for Cineworld Group, one of the world’s largest cinema chains.
  • B. Cinemastar
    Cinemastar is a line of hard disk drives produced by HGST, typically designed for consumer and multimedia applications.
  • C. Vides Cinematografica
    Vides Cinematografica was an Italian film production company active in the mid-20th century, known for producing notable Italian and international cinema.
  • D. Cinema International Corporation
    Cinema International Corporation was a major international film distribution company formed by the joint venture of major Hollywood studios to handle the overseas release of their movies in the 1970s and early 1980s.
  • E. Yara Cinema
    Yara Cinema is a prominent and historic movie theater in Havana, Cuba, known as a cultural landmark and popular gathering place in the Vedado district.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6daf2b7bc8190a3e73f3b24f0352b completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c758a0e5bc819098206940fc3ac623 completed March 28, 2026, 4:27 a.m.
NEDg Description generation batch_69c759553fe081909881c8d2ae680dfe completed March 28, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_69c759c79de48190bd3e079c07a9158a completed March 28, 2026, 4:32 a.m.
Created at: March 27, 2026, 2:30 p.m.