Triple

T10635743
Position Surface form Disambiguated ID Type / Status
Subject Nesodden E250574 entity
Predicate hasSettlement P1068 FINISHED
Object Fagerstrand
Fagerstrand is a village in Nesodden municipality in Viken county, Norway, located along the Oslofjord.
E875291 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: Fagerstrand | Statement: [Nesodden, hasSettlement, Fagerstrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fagerstrand
Context triple: [Nesodden, hasSettlement, Fagerstrand]
  • A. Fager
    Fager is a surname most notably associated with American television producer and former CBS News chairman Jeff Fager.
  • B. Fenstad
    Fenstad is a village in Nes municipality in Akershus, Norway.
  • C. Nister
    The Nister is a river in western Germany, known as a scenic tributary of the Sieg that flows through the Westerwald region.
  • D. Linderud
    Linderud is a residential neighborhood in Oslo, Norway, known for its apartment blocks, shopping center, and access to public transportation.
  • E. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • 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: Fagerstrand
Triple: [Nesodden, hasSettlement, Fagerstrand]
Generated description
Fagerstrand is a village in Nesodden municipality in Viken county, Norway, located along the Oslofjord.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fagerstrand
Target entity description: Fagerstrand is a village in Nesodden municipality in Viken county, Norway, located along the Oslofjord.
  • A. Fager
    Fager is a surname most notably associated with American television producer and former CBS News chairman Jeff Fager.
  • B. Fenstad
    Fenstad is a village in Nes municipality in Akershus, Norway.
  • C. Nister
    The Nister is a river in western Germany, known as a scenic tributary of the Sieg that flows through the Westerwald region.
  • D. Linderud
    Linderud is a residential neighborhood in Oslo, Norway, known for its apartment blocks, shopping center, and access to public transportation.
  • E. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfac70f481908363f9ac0b651fbe completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bc57a8081908abd73f4273d0666 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d96df03c2881909af8501ecf6ac180 completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d96f063d588190adcfd56b2b0afccf completed April 10, 2026, 9:43 p.m.
Created at: April 8, 2026, 9:03 p.m.