Triple

T155056
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Labour Party E3161 entity
Predicate foundedIn P41 FINISHED
Object Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
E22542 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: Arendal | Statement: [Norwegian Labour Party, foundedIn, Arendal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arendal
Context triple: [Norwegian Labour Party, foundedIn, Arendal]
  • A. Copenhagen
    Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Furnes (Veurne)
    Furnes (Veurne) is a historic town in West Flanders, Belgium, known for its well-preserved medieval architecture and role as a regional cultural center.
  • E. Venice of the North
    Venice of the North is a nickname commonly given to St. Petersburg, Russia, highlighting its extensive network of canals, rivers, and elegant bridges reminiscent of Venice.
  • 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: Arendal
Triple: [Norwegian Labour Party, foundedIn, Arendal]
Generated description
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arendal
Target entity description: Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • A. Copenhagen
    Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Furnes (Veurne)
    Furnes (Veurne) is a historic town in West Flanders, Belgium, known for its well-preserved medieval architecture and role as a regional cultural center.
  • E. Venice of the North
    Venice of the North is a nickname commonly given to St. Petersburg, Russia, highlighting its extensive network of canals, rivers, and elegant bridges reminiscent of Venice.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a2582eb6408190beb38213c7d7d968 completed Feb. 28, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2f0b399d0819088332903146ddf94 completed Feb. 28, 2026, 1:42 p.m.
NEDg Description generation batch_69a2f1617d1881908010a173098ad8a8 completed Feb. 28, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_69a2f1cf22f48190a7cc60661a61db4a completed Feb. 28, 2026, 1:46 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.