Triple

T3882258
Position Surface form Disambiguated ID Type / Status
Subject Akershus E92851 entity
Predicate contains P35 FINISHED
Object Nesodden
Nesodden is a municipality and peninsula in southeastern Norway, situated across the Oslofjord from the capital city of Oslo.
E394792 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: Nesodden | Statement: [Akershus, contains, Nesodden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nesodden
Context triple: [Akershus, contains, Nesodden]
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Sundbyvester
    Sundbyvester is a district of Copenhagen located on Amager Island, known primarily as a residential urban area.
  • C. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Vadsø
    Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
  • 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: Nesodden
Triple: [Akershus, contains, Nesodden]
Generated description
Nesodden is a municipality and peninsula in southeastern Norway, situated across the Oslofjord from the capital city of Oslo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nesodden
Target entity description: Nesodden is a municipality and peninsula in southeastern Norway, situated across the Oslofjord from the capital city of Oslo.
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Sundbyvester
    Sundbyvester is a district of Copenhagen located on Amager Island, known primarily as a residential urban area.
  • C. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Vadsø
    Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec8e8b3481909617ca0e37f8a6d4 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b512594fa081909ba2afad11f6ea59 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b513013db481908f8fb5f56470c0d0 completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b5137200a08190bd2a78398e03803e completed March 14, 2026, 7:51 a.m.
Created at: March 9, 2026, 3:20 p.m.