Triple

T13587882
Position Surface form Disambiguated ID Type / Status
Subject Wings Air E324616 entity
Predicate ICAOcode P419 FINISHED
Object WON
WON is the ICAO airline designator assigned to Wings Air, an Indonesian regional carrier.
 E1049479 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: WON | Statement: [Wings Air, ICAOcode, WON]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WON
Context triple: [Wings Air, ICAOcode, WON]
  • A. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • B. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • C. WUN
    WUN is the commonly used abbreviation for Western United FC, a professional soccer club based in Victoria, Australia that competes in the A-League Men.
  • D. WoS
    WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
  • E. WCON
    WCON is the informal station code used to refer to West Concord station, a commuter rail stop in Concord, Massachusetts.
  • 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: WON
Triple: [Wings Air, ICAOcode, WON]
Generated description
WON is the ICAO airline designator assigned to Wings Air, an Indonesian regional carrier.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WON
Target entity description: WON is the ICAO airline designator assigned to Wings Air, an Indonesian regional carrier.
  • A. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • B. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • C. WUN
    WUN is the commonly used abbreviation for Western United FC, a professional soccer club based in Victoria, Australia that competes in the A-League Men.
  • D. WoS
    WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
  • E. WCON
    WCON is the informal station code used to refer to West Concord station, a commuter rail stop in Concord, Massachusetts.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb054c6008190839384ce26e8f71a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc347b881908267455f3bdd50e8 completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77642e4b881909915c686a0d6c6fa completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f77923fd1481908af251a1dcbcf441 completed May 3, 2026, 4:34 p.m.
Created at: April 9, 2026, 9:49 p.m.