Triple

T6981711
Position Surface form Disambiguated ID Type / Status
Subject Trondheim Airport, Værnes E161861 entity
Predicate hasICAOcode P419 FINISHED
Object ENVA
ENVA is the ICAO airport code for Trondheim Airport, Værnes, a major international airport serving the Trondheim region in Norway.
 E632523 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: ENVA | Statement: [Trondheim Airport, Værnes, hasICAOcode, ENVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ENVA
Context triple: [Trondheim Airport, Værnes, hasICAOcode, ENVA]
  • A. ENBR
    ENBR is the ICAO airport code for Bergen Airport, Flesland, the main international airport serving Bergen, Norway.
  • B. Envall
    Envall is a Swedish surname most notably associated with automotive designer Björn Envall.
  • C. EGVA
    EGVA is the ICAO airport code for RAF Fairford, a Royal Air Force station in Gloucestershire, England used primarily by the United States Air Force for bomber and airlift operations.
  • D. Eco
    Eco is the proposed common currency intended to be adopted by member states of the Economic Community of West African States (ECOWAS) to facilitate regional economic integration.
  • E. Eco
    Eco is an Italian surname most famously borne by Umberto Eco, the renowned novelist, philosopher, and semiotician.
  • 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: ENVA
Triple: [Trondheim Airport, Værnes, hasICAOcode, ENVA]
Generated description
ENVA is the ICAO airport code for Trondheim Airport, Værnes, a major international airport serving the Trondheim region in Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ENVA
Target entity description: ENVA is the ICAO airport code for Trondheim Airport, Værnes, a major international airport serving the Trondheim region in Norway.
  • A. ENBR
    ENBR is the ICAO airport code for Bergen Airport, Flesland, the main international airport serving Bergen, Norway.
  • B. Envall
    Envall is a Swedish surname most notably associated with automotive designer Björn Envall.
  • C. EGVA
    EGVA is the ICAO airport code for RAF Fairford, a Royal Air Force station in Gloucestershire, England used primarily by the United States Air Force for bomber and airlift operations.
  • D. Eco
    Eco is the proposed common currency intended to be adopted by member states of the Economic Community of West African States (ECOWAS) to facilitate regional economic integration.
  • E. Eco
    Eco is an Italian surname most famously borne by Umberto Eco, the renowned novelist, philosopher, and semiotician.
  • 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_69c68855dc0481909b4c7e9e9ed273db completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db6d3f3c8190b0121f7934440c34 completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761c0ecd88190a684392aa6daf267 completed March 28, 2026, 5:06 a.m.
NEDg Description generation batch_69c76275a5f08190b71a59694ef4a1fd completed March 28, 2026, 5:09 a.m.
NED2 Entity disambiguation (via description) batch_69c762ee1a048190ada3e6fd850e468b completed March 28, 2026, 5:11 a.m.
Created at: March 27, 2026, 2:31 p.m.