Triple

T4307582
Position Surface form Disambiguated ID Type / Status
Subject Vitebsk Vostochny Airport E93992 entity
Predicate hasIATACode P2569 FINISHED
Object VTB
VTB is the IATA airport code assigned to Vitebsk Vostochny Airport in Belarus.
E429218 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: VTB | Statement: [Vitebsk Vostochny Airport, hasIATACode, VTB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VTB
Context triple: [Vitebsk Vostochny Airport, hasIATACode, VTB]
  • A. VTB Bank
    VTB Bank is one of Russia’s largest state-controlled financial institutions, offering a wide range of banking and financial services domestically and internationally.
  • B. VKO
    VKO is the IATA airport code for Vnukovo International Airport, one of Moscow’s major international airports in Russia.
  • C. Lebedev Holdings
    Lebedev Holdings is a media investment company controlled by the Lebedev family, best known for owning the London-based newspaper the Evening Standard.
  • D. ΦΒΚ
    ΦΒΚ is the Greek-letter abbreviation for Phi Beta Kappa, the oldest and one of the most prestigious academic honor societies in the United States, recognizing excellence in the liberal arts and sciences.
  • E. MKB Fakel
    MKB Fakel is a Russian aerospace company best known for developing and producing rocket and space propulsion systems, particularly electric thrusters for satellites.
  • 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: VTB
Triple: [Vitebsk Vostochny Airport, hasIATACode, VTB]
Generated description
VTB is the IATA airport code assigned to Vitebsk Vostochny Airport in Belarus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VTB
Target entity description: VTB is the IATA airport code assigned to Vitebsk Vostochny Airport in Belarus.
  • A. VTB Bank
    VTB Bank is one of Russia’s largest state-controlled financial institutions, offering a wide range of banking and financial services domestically and internationally.
  • B. VKO
    VKO is the IATA airport code for Vnukovo International Airport, one of Moscow’s major international airports in Russia.
  • C. Lebedev Holdings
    Lebedev Holdings is a media investment company controlled by the Lebedev family, best known for owning the London-based newspaper the Evening Standard.
  • D. ΦΒΚ
    ΦΒΚ is the Greek-letter abbreviation for Phi Beta Kappa, the oldest and one of the most prestigious academic honor societies in the United States, recognizing excellence in the liberal arts and sciences.
  • E. MKB Fakel
    MKB Fakel is a Russian aerospace company best known for developing and producing rocket and space propulsion systems, particularly electric thrusters for satellites.
  • 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350d2af088190ad7cb035d6e0f8c2 completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c756809c8190af90c91ec7883e55 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c804f3f881908dd2d020d07c4859 completed March 14, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84e48b8819080571f995d8baf13 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:11 p.m.