Triple

T2411474
Position Surface form Disambiguated ID Type / Status
Subject Wingo E52199 entity
Predicate callsign P1565 FINISHED
Object WINGO
WINGO is the radio callsign used by Wingo, a low-cost Colombian airline operating domestic and international flights in Latin America.
 E263961 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: WINGO | Statement: [Wingo, callsign, WINGO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WINGO
Context triple: [Wingo, callsign, WINGO]
  • A. Wild Wing
    Wild Wing is the anthropomorphic duck mascot of the NHL's Anaheim Ducks, known for his energetic in-game antics and appearances at team events.
  • B. Wing
    Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
  • C. Wing
    Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
  • D. ANA Wings
    ANA Wings is a Japanese regional airline operating domestic feeder and short-haul services on behalf of All Nippon Airways.
  • E. Under a Wing
    "Under a Wing" is a memoir by Reeve Lindbergh reflecting on her childhood and family life as the daughter of famed aviator Charles Lindbergh and writer Anne Morrow Lindbergh.
  • 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: WINGO
Triple: [Wingo, callsign, WINGO]
Generated description
WINGO is the radio callsign used by Wingo, a low-cost Colombian airline operating domestic and international flights in Latin America.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WINGO
Target entity description: WINGO is the radio callsign used by Wingo, a low-cost Colombian airline operating domestic and international flights in Latin America.
  • A. Wild Wing
    Wild Wing is the anthropomorphic duck mascot of the NHL's Anaheim Ducks, known for his energetic in-game antics and appearances at team events.
  • B. Wing
    Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
  • C. Wing
    Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
  • D. ANA Wings
    ANA Wings is a Japanese regional airline operating domestic feeder and short-haul services on behalf of All Nippon Airways.
  • E. Under a Wing
    "Under a Wing" is a memoir by Reeve Lindbergh reflecting on her childhood and family life as the daughter of famed aviator Charles Lindbergh and writer Anne Morrow Lindbergh.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc928fd608190885fcde6746a06bc completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3f00cc481909c2841a6f2ebadad completed March 9, 2026, 11:50 a.m.
NEDg Description generation batch_69aeb630b9588190a09652e9a3e65731 completed March 9, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_69aeb68465608190b40e8be870b54ffb completed March 9, 2026, 12:01 p.m.
Created at: March 6, 2026, 9:41 p.m.