Triple

T3687687
Position Surface form Disambiguated ID Type / Status
Subject Alta E78263 entity
Predicate hasAirport P105 FINISHED
Object Alta Airport
Alta Airport is a regional airport in Alta, Norway, serving as an important air transport hub for the Finnmark region.
E380405 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: Alta Airport | Statement: [Alta, hasAirport, Alta Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alta Airport
Context triple: [Alta, hasAirport, Alta Airport]
  • A. Hammerfest Airport
    Hammerfest Airport is a regional airport in Hammerfest, Norway, providing scheduled domestic flights that connect the town to other parts of the country.
  • B. Henry E. Rohlsen Airport
    Henry E. Rohlsen Airport is a public airport on the island of St. Croix that serves as one of the main air gateways to the U.S. Virgin Islands.
  • C. Pico Airport
    Pico Airport is a regional airport in the Azores archipelago of Portugal that serves Pico Island with domestic flights and limited international connections.
  • D. El Lencero Airport
    El Lencero Airport is a small regional airport serving the city of Xalapa and the surrounding area in the state of Veracruz, Mexico.
  • E. HEF Airport
    HEF Airport is the regional public airport serving Manassas, Virginia, handling general aviation and some corporate and charter traffic for the Washington, D.C. metropolitan area.
  • 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: Alta Airport
Triple: [Alta, hasAirport, Alta Airport]
Generated description
Alta Airport is a regional airport in Alta, Norway, serving as an important air transport hub for the Finnmark region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alta Airport
Target entity description: Alta Airport is a regional airport in Alta, Norway, serving as an important air transport hub for the Finnmark region.
  • A. Hammerfest Airport
    Hammerfest Airport is a regional airport in Hammerfest, Norway, providing scheduled domestic flights that connect the town to other parts of the country.
  • B. Henry E. Rohlsen Airport
    Henry E. Rohlsen Airport is a public airport on the island of St. Croix that serves as one of the main air gateways to the U.S. Virgin Islands.
  • C. Pico Airport
    Pico Airport is a regional airport in the Azores archipelago of Portugal that serves Pico Island with domestic flights and limited international connections.
  • D. El Lencero Airport
    El Lencero Airport is a small regional airport serving the city of Xalapa and the surrounding area in the state of Veracruz, Mexico.
  • E. HEF Airport
    HEF Airport is the regional public airport serving Manassas, Virginia, handling general aviation and some corporate and charter traffic for the Washington, D.C. metropolitan area.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c7e2bc81909356c8b0ed90feed completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3c10f6481908feed99cddc56d47 completed March 14, 2026, 2:11 a.m.
NEDg Description generation batch_69b4c7bd861c8190a1a7887f6d7fd6de completed March 14, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69b4c83085488190a48c6e4786d275e2 completed March 14, 2026, 2:30 a.m.
Created at: March 8, 2026, 3:26 p.m.