Triple

T16045821
Position Surface form Disambiguated ID Type / Status
Subject Finnås E389214 entity
Predicate hasCountyCode P10086 FINISHED
Object Vestland (NO-46)
Vestland (NO-46) is a county in western Norway known for its dramatic fjord landscapes, coastal islands, and the city of Bergen.
 E1191268 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: Vestland (NO-46) | Statement: [Finnås, hasCountyCode, Vestland (NO-46)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vestland (NO-46)
Context triple: [Finnås, hasCountyCode, Vestland (NO-46)]
  • A. MS Vesterålen
    MS Vesterålen is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten coastal route, known for its intimate size and classic working-ship character.
  • B. MS Finnmarken
    MS Finnmarken is a Norwegian coastal cruise ship operated on the Hurtigruten coastal route, offering passenger and cargo services along Norway’s coastline.
  • C. Vestnes
    Vestnes is a municipality and village in western Norway known for its coastal location along the Romsdalsfjord and its role as a local administrative and service center.
  • D. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • E. Ulstein
    Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
  • 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: Vestland (NO-46)
Triple: [Finnås, hasCountyCode, Vestland (NO-46)]
Generated description
Vestland (NO-46) is a county in western Norway known for its dramatic fjord landscapes, coastal islands, and the city of Bergen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vestland (NO-46)
Target entity description: Vestland (NO-46) is a county in western Norway known for its dramatic fjord landscapes, coastal islands, and the city of Bergen.
  • A. MS Vesterålen
    MS Vesterålen is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten coastal route, known for its intimate size and classic working-ship character.
  • B. MS Finnmarken
    MS Finnmarken is a Norwegian coastal cruise ship operated on the Hurtigruten coastal route, offering passenger and cargo services along Norway’s coastline.
  • C. Vestnes
    Vestnes is a municipality and village in western Norway known for its coastal location along the Romsdalsfjord and its role as a local administrative and service center.
  • D. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • E. Ulstein
    Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1835dd9a0819087e362cf5770232a completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbdbcf248190b7122d61d857e806 completed May 10, 2026, 1:14 a.m.
NEDg Description generation batch_69ffdcdb551c8190b367407b749314e8 completed May 10, 2026, 1:18 a.m.
NED2 Entity disambiguation (via description) batch_69ffddbfaf088190a644e7898f995c1d completed May 10, 2026, 1:22 a.m.
Created at: April 10, 2026, 4:56 a.m.