Triple

T5588659
Position Surface form Disambiguated ID Type / Status
Subject Heby Municipality E146820 entity
Predicate hasSettlement P1068 FINISHED
Object Tärnsjö
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
 E536691 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: Tärnsjö | Statement: [Heby Municipality, hasSettlement, Tärnsjö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tärnsjö
Context triple: [Heby Municipality, hasSettlement, Tärnsjö]
  • A. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • B. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • C. Hovsjö
    Hovsjö is a residential district in the city of Södertälje, Sweden, known for its large-scale housing estates and diverse population.
  • D. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • E. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • 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: Tärnsjö
Triple: [Heby Municipality, hasSettlement, Tärnsjö]
Generated description
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tärnsjö
Target entity description: Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
  • A. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • B. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • C. Hovsjö
    Hovsjö is a residential district in the city of Södertälje, Sweden, known for its large-scale housing estates and diverse population.
  • D. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • E. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0209e892c8190b936a05ef2a14d36 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d2f8710819094f5d052b767b9a6 completed March 22, 2026, 8:12 p.m.
NEDg Description generation batch_69c04e88680c8190845723f52c060fb7 completed March 22, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_69c04f7856848190a835c3ee0a32f649 completed March 22, 2026, 8:22 p.m.
Created at: March 22, 2026, 3:38 p.m.