Triple

T1345310
Position Surface form Disambiguated ID Type / Status
Subject Vueling E28556 entity
Predicate ICAOcode P419 FINISHED
Object VLG
VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
E153467 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: VLG | Statement: [Vueling, ICAOcode, VLG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VLG
Context triple: [Vueling, ICAOcode, VLG]
  • A. VLKSM
    VLKSM was the Russian abbreviation for the All-Union Leninist Young Communist League, the Soviet Union’s official youth organization affiliated with the Communist Party.
  • B. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • C. VWAG
    VWAG is the stock ticker symbol under which the multinational automotive manufacturer Volkswagen Group is publicly traded.
  • D. LGW
    LGW is the three-letter IATA airport code for London Gatwick Airport, a major international airport serving the London metropolitan area in the United Kingdom.
  • E. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • 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: VLG
Triple: [Vueling, ICAOcode, VLG]
Generated description
VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VLG
Target entity description: VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
  • A. VLKSM
    VLKSM was the Russian abbreviation for the All-Union Leninist Young Communist League, the Soviet Union’s official youth organization affiliated with the Communist Party.
  • B. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • C. VWAG
    VWAG is the stock ticker symbol under which the multinational automotive manufacturer Volkswagen Group is publicly traded.
  • D. LGW
    LGW is the three-letter IATA airport code for London Gatwick Airport, a major international airport serving the London metropolitan area in the United Kingdom.
  • E. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c23d696c8190bb688274280cb680 completed March 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc6351cbc81909e2ffc692ee92b54 completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6af0db88190a02936072783553e completed March 8, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69acc722d8608190acbef82f180b75d1 completed March 8, 2026, 12:47 a.m.
Created at: March 1, 2026, 7:56 p.m.