Triple

T15040406
Position Surface form Disambiguated ID Type / Status
Subject Söderort E378584 entity
Predicate hasPart P35 FINISHED
Object Fagersjö
Fagersjö is a residential district in southern Stockholm, Sweden, known for its proximity to lakes and green areas.
E1138040 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: Fagersjö | Statement: [Söderort, hasPart, Fagersjö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fagersjö
Context triple: [Söderort, hasPart, Fagersjö]
  • A. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • B. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • C. Tärnsjö
    Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
  • D. Såtenäs
    Såtenäs is a locality in western Sweden best known as a major Swedish Air Force base and home of the F 7 Wing.
  • E. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • 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: Fagersjö
Triple: [Söderort, hasPart, Fagersjö]
Generated description
Fagersjö is a residential district in southern Stockholm, Sweden, known for its proximity to lakes and green areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fagersjö
Target entity description: Fagersjö is a residential district in southern Stockholm, Sweden, known for its proximity to lakes and green areas.
  • A. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • B. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • C. Tärnsjö
    Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
  • D. Såtenäs
    Såtenäs is a locality in western Sweden best known as a major Swedish Air Force base and home of the F 7 Wing.
  • E. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82e79a481908ddb9609af8c4407 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69feb7db6f0081909ab35435c1e4ad13 completed May 9, 2026, 4:28 a.m.
NEDg Description generation batch_69feb945ec7481909f4bfbf628985af8 completed May 9, 2026, 4:34 a.m.
NED2 Entity disambiguation (via description) batch_69feb9a010ec819087df75319550cc88 completed May 9, 2026, 4:35 a.m.
Created at: April 10, 2026, 3 a.m.