Triple

T468318
Position Surface form Disambiguated ID Type / Status
Subject Jet2.com E8498 entity
Predicate callsign P1565 FINISHED
Object CHANNEX
CHANNEX is the radio callsign used by the British low-cost airline Jet2.com during air traffic communications.
 E58610 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: CHANNEX | Statement: [Jet2.com, callsign, CHANNEX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CHANNEX
Context triple: [Jet2.com, callsign, CHANNEX]
  • A. Channel
    Channel is a common alternative name for the English Channel, the narrow arm of the Atlantic Ocean that separates southern England from northern France.
  • B. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • C. .ch
    .ch is the country code top-level domain (ccTLD) for Switzerland, derived from the Latin name "Confoederatio Helvetica."
  • D. BCCh
    BCCh is the acronym for the Central Bank of Chile, the country’s autonomous monetary authority responsible for maintaining price stability and financial system soundness.
  • E. CNE
    CNE is a large annual fair and exhibition held in Toronto, Canada, featuring rides, games, concerts, food, and cultural events.
  • 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: CHANNEX
Triple: [Jet2.com, callsign, CHANNEX]
Generated description
CHANNEX is the radio callsign used by the British low-cost airline Jet2.com during air traffic communications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CHANNEX
Target entity description: CHANNEX is the radio callsign used by the British low-cost airline Jet2.com during air traffic communications.
  • A. Channel
    Channel is a common alternative name for the English Channel, the narrow arm of the Atlantic Ocean that separates southern England from northern France.
  • B. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • C. .ch
    .ch is the country code top-level domain (ccTLD) for Switzerland, derived from the Latin name "Confoederatio Helvetica."
  • D. BCCh
    BCCh is the acronym for the Central Bank of Chile, the country’s autonomous monetary authority responsible for maintaining price stability and financial system soundness.
  • E. CNE
    CNE is a large annual fair and exhibition held in Toronto, Canada, featuring rides, games, concerts, food, and cultural events.
  • 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_69a2e7f3aeb48190a19453e3a043f486 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efd9bea081909ee782840f3da12b completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a45802334881908eb49c09f68c1a22 completed March 1, 2026, 3:15 p.m.
NEDg Description generation batch_69a45bf215408190b9d6adbfb12b2df8 completed March 1, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_69a45c5603f881908c48380212c69db7 completed March 1, 2026, 3:33 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.