Triple

T4376847
Position Surface form Disambiguated ID Type / Status
Subject Gothenburg Landvetter Airport E99027 entity
Predicate locatedIn P40 FINISHED
Object Landvetter
Landvetter is a locality in western Sweden that serves as a key transport hub for the Gothenburg region, best known for hosting Gothenburg Landvetter Airport.
E435616 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: Landvetter | Statement: [Gothenburg Landvetter Airport, locatedIn, Landvetter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landvetter
Context triple: [Gothenburg Landvetter Airport, locatedIn, Landvetter]
  • A. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • B. Vallentuna
    Vallentuna is a locality in Stockholm County, Sweden, known as a suburban community within the Stockholm metropolitan area.
  • C. Torvastad
    Torvastad is a coastal village in Karmøy municipality in Rogaland county, southwestern Norway.
  • D. Vallader
    Vallader is a major dialect of the Romansh language spoken primarily in Switzerland’s Lower Engadine region and used in local literature and education.
  • E. Espevær
    Espevær is a small island and fishing village in Vestland county, Norway, known for its traditional coastal culture and scenic maritime environment.
  • 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: Landvetter
Triple: [Gothenburg Landvetter Airport, locatedIn, Landvetter]
Generated description
Landvetter is a locality in western Sweden that serves as a key transport hub for the Gothenburg region, best known for hosting Gothenburg Landvetter Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Landvetter
Target entity description: Landvetter is a locality in western Sweden that serves as a key transport hub for the Gothenburg region, best known for hosting Gothenburg Landvetter Airport.
  • A. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • B. Vallentuna
    Vallentuna is a locality in Stockholm County, Sweden, known as a suburban community within the Stockholm metropolitan area.
  • C. Torvastad
    Torvastad is a coastal village in Karmøy municipality in Rogaland county, southwestern Norway.
  • D. Vallader
    Vallader is a major dialect of the Romansh language spoken primarily in Switzerland’s Lower Engadine region and used in local literature and education.
  • E. Espevær
    Espevær is a small island and fishing village in Vestland county, Norway, known for its traditional coastal culture and scenic maritime environment.
  • 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_69b3454ea8f48190a49c2436624d6ef6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3523ed220819090cef1a7933489d9 completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e51907688190ad964d341eb84529 completed March 14, 2026, 10:45 p.m.
NEDg Description generation batch_69b5e5d675808190a5a9767f253f0178 completed March 14, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_69b5e66837e081908ac5a0079485cd18 completed March 14, 2026, 10:51 p.m.
Created at: March 12, 2026, 11:18 p.m.