Triple

T1629316
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Baiyun International Airport E35221 entity
Predicate hubFor P423 FINISHED
Object 9 Air
9 Air is a Chinese low-cost airline based in Guangzhou that operates domestic and regional passenger flights.
 E185256 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: 9 Air | Statement: [Guangzhou Baiyun International Airport, hubFor, 9 Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 9 Air
Context triple: [Guangzhou Baiyun International Airport, hubFor, 9 Air]
  • A. Aero
    Aero is a high-performance, sport-oriented trim level used by Saab for its 9-3 and other models, typically featuring more powerful engines and upgraded equipment.
  • B. Air
    "Air" is a 2023 biographical sports drama film directed by Ben Affleck that chronicles Nike's pursuit of a young Michael Jordan, in which Matt Damon stars as talent scout Sonny Vaccaro.
  • C. J-Air
    J-Air is a Japanese regional airline operating domestic feeder and short-haul routes on behalf of Japan Airlines.
  • D. Luft
    Luft is a surname most notably associated with Sid Luft, the American film producer and third husband of entertainer Judy Garland.
  • E. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • 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: 9 Air
Triple: [Guangzhou Baiyun International Airport, hubFor, 9 Air]
Generated description
9 Air is a Chinese low-cost airline based in Guangzhou that operates domestic and regional passenger flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 9 Air
Target entity description: 9 Air is a Chinese low-cost airline based in Guangzhou that operates domestic and regional passenger flights.
  • A. Aero
    Aero is a high-performance, sport-oriented trim level used by Saab for its 9-3 and other models, typically featuring more powerful engines and upgraded equipment.
  • B. Air
    "Air" is a 2023 biographical sports drama film directed by Ben Affleck that chronicles Nike's pursuit of a young Michael Jordan, in which Matt Damon stars as talent scout Sonny Vaccaro.
  • C. J-Air
    J-Air is a Japanese regional airline operating domestic feeder and short-haul routes on behalf of Japan Airlines.
  • D. Luft
    Luft is a surname most notably associated with Sid Luft, the American film producer and third husband of entertainer Judy Garland.
  • E. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909f257948190b3398fd6dc91f586 completed March 5, 2026, 4:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58d5acd8819090c51678ce0f63f0 completed March 8, 2026, 11:09 a.m.
NEDg Description generation batch_69ad5a619da481908d66837ea94c91cf completed March 8, 2026, 11:15 a.m.
NED2 Entity disambiguation (via description) batch_69ad5b41a68c8190ba293d8e8c35521b completed March 8, 2026, 11:19 a.m.
Created at: March 4, 2026, 7:28 p.m.