Triple

T11463307
Position Surface form Disambiguated ID Type / Status
Subject Ovda Airport E271714 entity
Predicate hasIATAcode P2569 FINISHED
Object VDA
VDA is the IATA airport code for Ovda Airport, a former joint military-civilian airfield in southern Israel that has handled international charter and low-cost flights.
E927861 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: VDA | Statement: [Ovda Airport, hasIATAcode, VDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VDA
Context triple: [Ovda Airport, hasIATAcode, VDA]
  • A. VAND
    VAND is the ICAO airport code assigned to Shri Guru Gobind Singh Ji Airport in India.
  • B. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • C. VAN
    VAN is the standard abbreviation used for the Vancouver Canadians, a Minor League Baseball team based in Vancouver, British Columbia.
  • D. DAF
    DAF is the acronym for the German Labour Front, the Nazi-era organization that replaced trade unions in Germany and controlled workers and employers under a state-run labor system.
  • E. DAF
    DAF is the OECD’s Directorate for Financial and Enterprise Affairs, responsible for developing international policies and standards on finance, corporate governance, competition, and investment.
  • 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: VDA
Triple: [Ovda Airport, hasIATAcode, VDA]
Generated description
VDA is the IATA airport code for Ovda Airport, a former joint military-civilian airfield in southern Israel that has handled international charter and low-cost flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VDA
Target entity description: VDA is the IATA airport code for Ovda Airport, a former joint military-civilian airfield in southern Israel that has handled international charter and low-cost flights.
  • A. VAND
    VAND is the ICAO airport code assigned to Shri Guru Gobind Singh Ji Airport in India.
  • B. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • C. VAN
    VAN is the standard abbreviation used for the Vancouver Canadians, a Minor League Baseball team based in Vancouver, British Columbia.
  • D. DAF
    DAF is the acronym for the German Labour Front, the Nazi-era organization that replaced trade unions in Germany and controlled workers and employers under a state-run labor system.
  • E. DAF
    DAF is the OECD’s Directorate for Financial and Enterprise Affairs, responsible for developing international policies and standards on finance, corporate governance, competition, and investment.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f488248190b9f603cd31c72174 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e92a7c2881908d85009a6069b2e4 completed April 20, 2026, 8:51 a.m.
NEDg Description generation batch_69e5f1593c2c8190885f80ad5eeba3ec completed April 20, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69e5f87bbd988190ac388a3c34b2e95a completed April 20, 2026, 9:57 a.m.
Created at: April 8, 2026, 9:35 p.m.