Triple

T15333712
Position Surface form Disambiguated ID Type / Status
Subject Hordaland E366605 entity
Predicate traditionalDistrict P49478 FINISHED
Object Nordhordland
Nordhordland is a traditional district in western Norway known for its coastal landscapes, fjords, and proximity to the city of Bergen.
E1180814 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: Nordhordland | Statement: [Hordaland, traditionalDistrict, Nordhordland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordhordland
Context triple: [Hordaland, traditionalDistrict, Nordhordland]
  • A. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • B. Midthordland
    Midthordland is a traditional district in western Norway, forming part of the coastal and fjord landscape around the city of Bergen.
  • C. Hordaland
    Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • D. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • E. Fjordane
    Fjordane is a traditional district in western Norway known for its dramatic fjord landscapes and coastal scenery.
  • 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: Nordhordland
Triple: [Hordaland, traditionalDistrict, Nordhordland]
Generated description
Nordhordland is a traditional district in western Norway known for its coastal landscapes, fjords, and proximity to the city of Bergen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nordhordland
Target entity description: Nordhordland is a traditional district in western Norway known for its coastal landscapes, fjords, and proximity to the city of Bergen.
  • A. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • B. Midthordland
    Midthordland is a traditional district in western Norway, forming part of the coastal and fjord landscape around the city of Bergen.
  • C. Hordaland
    Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • D. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • E. Fjordane
    Fjordane is a traditional district in western Norway known for its dramatic fjord landscapes and coastal scenery.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa92e5f5c81908f54e91b7f16607e completed May 9, 2026, 9:37 p.m.
NEDg Description generation batch_69ffaa279e888190a1c8d95a10b77766 completed May 9, 2026, 9:41 p.m.
NED2 Entity disambiguation (via description) batch_69ffaaa92a648190a09829ef3197223c completed May 9, 2026, 9:44 p.m.
Created at: April 10, 2026, 3:17 a.m.