Triple

T19033696
Position Surface form Disambiguated ID Type / Status
Subject Vilnius Airport E465809 entity
Predicate IATAcode P418 FINISHED
Object VNO
VNO is the IATA airport code for Vilnius Airport, the main international airport serving Lithuania’s capital city.
E1354899 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: VNO | Statement: [Vilnius Airport, IATAcode, VNO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VNO
Context triple: [Vilnius Airport, IATAcode, VNO]
  • A. VNU
    VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
  • B. VNK
    VNK is the abbreviation for the Prime Minister’s Office of Finland, which supports the government and coordinates its activities.
  • C. NVO
    NVO is the stock ticker symbol for Novo Nordisk, a global pharmaceutical company best known for its diabetes care products.
  • D. VNNG
    VNNG is the ICAO airport code for Nepalgunj Airport in Nepal, a regional hub serving the city of Nepalgunj and surrounding areas.
  • E. VOI
    VOI is the ICAO airline designator used to identify Volaris, a Mexican low-cost carrier, in aviation operations and communications.
  • 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: VNO
Triple: [Vilnius Airport, IATAcode, VNO]
Generated description
VNO is the IATA airport code for Vilnius Airport, the main international airport serving Lithuania’s capital city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VNO
Target entity description: VNO is the IATA airport code for Vilnius Airport, the main international airport serving Lithuania’s capital city.
  • A. VNU
    VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
  • B. VNK
    VNK is the abbreviation for the Prime Minister’s Office of Finland, which supports the government and coordinates its activities.
  • C. NVO
    NVO is the stock ticker symbol for Novo Nordisk, a global pharmaceutical company best known for its diabetes care products.
  • D. VNNG
    VNNG is the ICAO airport code for Nepalgunj Airport in Nepal, a regional hub serving the city of Nepalgunj and surrounding areas.
  • E. VOI
    VOI is the ICAO airline designator used to identify Volaris, a Mexican low-cost carrier, in aviation operations and communications.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d741cabc8190900e12265ad269f8 completed April 20, 2026, 7:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05be5cb2b08190aa82bc001542528c completed May 14, 2026, 12:21 p.m.
NEDg Description generation batch_6a05bf2efb588190b530183f406d3594 completed May 14, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a05bfc5e5448190baca381badc5be79 completed May 14, 2026, 12:27 p.m.
Created at: April 10, 2026, 12:02 p.m.