Triple

T468320
Position Surface form Disambiguated ID Type / Status
Subject Jet2.com E8498 entity
Predicate formerName P65 FINISHED
Object Channel Express
Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
 E58611 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: Channel Express | Statement: [Jet2.com, formerName, Channel Express]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Channel Express
Context triple: [Jet2.com, formerName, Channel Express]
  • A. DHL
    DHL is the Dag Hammarskjöld Library, the United Nations’ main research and information resource center located at its headquarters in New York.
  • B. HK Express
    HK Express is a Hong Kong-based low-cost airline operating regional flights across Asia.
  • C. FedEx
    FedEx is a global courier delivery services company known for its overnight shipping and pioneering real-time package tracking.
  • D. United Parcel Service (UPS)
    United Parcel Service (UPS) is a global package delivery and supply chain management company known for its extensive logistics network and brown delivery trucks.
  • E. USPS Retail Ground
    USPS Retail Ground is an economical U.S. Postal Service shipping option for sending larger, heavier packages over land within the United States.
  • 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: Channel Express
Triple: [Jet2.com, formerName, Channel Express]
Generated description
Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Channel Express
Target entity description: Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
  • A. DHL
    DHL is the Dag Hammarskjöld Library, the United Nations’ main research and information resource center located at its headquarters in New York.
  • B. HK Express
    HK Express is a Hong Kong-based low-cost airline operating regional flights across Asia.
  • C. FedEx
    FedEx is a global courier delivery services company known for its overnight shipping and pioneering real-time package tracking.
  • D. United Parcel Service (UPS)
    United Parcel Service (UPS) is a global package delivery and supply chain management company known for its extensive logistics network and brown delivery trucks.
  • E. USPS Retail Ground
    USPS Retail Ground is an economical U.S. Postal Service shipping option for sending larger, heavier packages over land within the United States.
  • 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.