Triple

T7266622
Position Surface form Disambiguated ID Type / Status
Subject Blekinge E160990 entity
Predicate containsCity P294 FINISHED
Object Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
 E669417 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: Ronneby | Statement: [Blekinge, containsCity, Ronneby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ronneby
Context triple: [Blekinge, containsCity, Ronneby]
  • A. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • B. Nykvarn
    Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
  • C. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • D. Nässjö
    Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
  • E. Mörbylånga
    Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
  • 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: Ronneby
Triple: [Blekinge, containsCity, Ronneby]
Generated description
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ronneby
Target entity description: Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
  • A. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • B. Nykvarn
    Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
  • C. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • D. Nässjö
    Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
  • E. Mörbylånga
    Mörbylånga is a small coastal town on the Swedish island of Öland, known as a local center near the vast limestone plain of Stora Alvaret.
  • 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae64e54819096b27c7b09060afa completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c845df01dc8190ac219c0bb87bd83c completed March 28, 2026, 9:19 p.m.
NEDg Description generation batch_69c846b326088190b93a32c70bcc97ca completed March 28, 2026, 9:22 p.m.
NED2 Entity disambiguation (via description) batch_69c8479490688190bc56b5a21d779b18 completed March 28, 2026, 9:26 p.m.
Created at: March 27, 2026, 2:58 p.m.