Triple

T1837454
Position Surface form Disambiguated ID Type / Status
Subject Finland Swedish E41096 entity
Predicate hasDialect P4251 FINISHED
Object Åboland Swedish
Åboland Swedish is a regional variety of Swedish spoken in the Åboland (Turunmaa) archipelago area of southwestern Finland.
 E205323 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: Åboland Swedish | Statement: [Finland Swedish, hasDialect, Åboland Swedish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Åboland Swedish
Context triple: [Finland Swedish, hasDialect, Åboland Swedish]
  • A. Uppland
    Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
  • B. Swedavia
    Swedavia is a Swedish state-owned company that owns, operates, and develops several of Sweden’s major airports.
  • C. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • D. Bohuslän
    Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
  • E. Skarpö
    Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
  • 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: Åboland Swedish
Triple: [Finland Swedish, hasDialect, Åboland Swedish]
Generated description
Åboland Swedish is a regional variety of Swedish spoken in the Åboland (Turunmaa) archipelago area of southwestern Finland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Åboland Swedish
Target entity description: Åboland Swedish is a regional variety of Swedish spoken in the Åboland (Turunmaa) archipelago area of southwestern Finland.
  • A. Uppland
    Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
  • B. Swedavia
    Swedavia is a Swedish state-owned company that owns, operates, and develops several of Sweden’s major airports.
  • C. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • D. Bohuslän
    Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
  • E. Skarpö
    Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0380a4c81909a2ad0bfd97c884a completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9b6dc9481908a83e60aee326bc4 completed March 8, 2026, 7:10 p.m.
NEDg Description generation batch_69adcaef04e88190a88f789a6370bafb completed March 8, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69adcb8e053c819082a3d4b36afe35be completed March 8, 2026, 7:18 p.m.
Created at: March 4, 2026, 7:33 p.m.