Triple

T13799329
Position Surface form Disambiguated ID Type / Status
Subject Lake Vänern E331596 entity
Predicate hasIsland P970 FINISHED
Object Brommö
Brommö is a Swedish island located in Lake Vänern, known for its forests, sandy beaches, and nature reserves.
E1062007 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: Brommö | Statement: [Lake Vänern, hasIsland, Brommö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brommö
Context triple: [Lake Vänern, hasIsland, Brommö]
  • A. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • B. Mjölby
    Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
  • C. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • D. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • E. Mönsterås
    Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
  • 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: Brommö
Triple: [Lake Vänern, hasIsland, Brommö]
Generated description
Brommö is a Swedish island located in Lake Vänern, known for its forests, sandy beaches, and nature reserves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brommö
Target entity description: Brommö is a Swedish island located in Lake Vänern, known for its forests, sandy beaches, and nature reserves.
  • A. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • B. Mjölby
    Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
  • C. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • D. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • E. Mönsterås
    Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b0893a20819081d4001b8dbc9c36 completed May 3, 2026, 8:31 p.m.
NEDg Description generation batch_69f7b138fda88190b2b7ffb51ce02a40 completed May 3, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7b28ca218819097fc35042d3b278a completed May 3, 2026, 8:39 p.m.
Created at: April 9, 2026, 10:11 p.m.