Triple

T3145080
Position Surface form Disambiguated ID Type / Status
Subject Oppland E65743 entity
Predicate borderedBy P224 FINISHED
Object Hordaland
Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
 E366605 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: Hordaland | Statement: [Oppland, borderedBy, Hordaland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hordaland
Context triple: [Oppland, borderedBy, Hordaland]
  • A. Rogaland
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • B. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • C. Aust-Agder
    Aust-Agder was a former county in southern Norway known for its coastal towns, forests, and role in the country’s maritime and timber industries.
  • D. Agder
    Agder is a county in southern Norway known for its long coastline, maritime heritage, and popular coastal towns and islands.
  • E. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • 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: Hordaland
Triple: [Oppland, borderedBy, Hordaland]
Generated description
Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hordaland
Target entity description: Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • A. Rogaland
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • B. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • C. Aust-Agder
    Aust-Agder was a former county in southern Norway known for its coastal towns, forests, and role in the country’s maritime and timber industries.
  • D. Agder
    Agder is a county in southern Norway known for its long coastline, maritime heritage, and popular coastal towns and islands.
  • E. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59797788190a8d71262888c5df0 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38babb044819098f887ac4fb0bab2 completed March 13, 2026, 3:59 a.m.
NEDg Description generation batch_69b38c9f4a088190873eeb5cd06597ea completed March 13, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69b38ceb64b881908e2ba9a129ff4cc9 completed March 13, 2026, 4:04 a.m.
Created at: March 8, 2026, 3:05 p.m.