Triple

T9048673
Position Surface form Disambiguated ID Type / Status
Subject Vanilla Air E216825 entity
Predicate ICAOcode P419 FINISHED
Object VNL
VNL is the ICAO airline designator assigned to Vanilla Air, a former Japanese low-cost carrier.
 E774481 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: VNL | Statement: [Vanilla Air, ICAOcode, VNL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VNL
Context triple: [Vanilla Air, ICAOcode, VNL]
  • A. VNLK
    VNLK is the ICAO airport code for Tenzing-Hillary Airport, the small but famous high-altitude airfield serving Lukla in Nepal’s Everest region.
  • B. VVNB
    VVNB is the ICAO airport code assigned to Noi Bai International Airport, the main international gateway serving Hanoi, Vietnam.
  • C. VNM
    VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
  • D. VNU
    VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
  • E. VRN
    VRN is the public transport association serving Germany’s Rhine-Neckar metropolitan region, coordinating regional and local transit services across multiple states.
  • 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: VNL
Triple: [Vanilla Air, ICAOcode, VNL]
Generated description
VNL is the ICAO airline designator assigned to Vanilla Air, a former Japanese low-cost carrier.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VNL
Target entity description: VNL is the ICAO airline designator assigned to Vanilla Air, a former Japanese low-cost carrier.
  • A. VNLK
    VNLK is the ICAO airport code for Tenzing-Hillary Airport, the small but famous high-altitude airfield serving Lukla in Nepal’s Everest region.
  • B. VVNB
    VVNB is the ICAO airport code assigned to Noi Bai International Airport, the main international gateway serving Hanoi, Vietnam.
  • C. VNM
    VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
  • D. VNU
    VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
  • E. VRN
    VRN is the public transport association serving Germany’s Rhine-Neckar metropolitan region, coordinating regional and local transit services across multiple states.
  • 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_69ca83d362e88190ae44b4e4dc194209 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6b51aa708190a37feecfd8deed2f completed April 1, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfebc0fd648190b0dd6cf62605b98f completed April 3, 2026, 4:33 p.m.
NEDg Description generation batch_69cfed4fb6cc8190bb97345dd392b25b completed April 3, 2026, 4:39 p.m.
NED2 Entity disambiguation (via description) batch_69cfedf299908190852cc627fd7134b9 completed April 3, 2026, 4:42 p.m.
Created at: March 30, 2026, 7:09 p.m.