Triple

T3882442
Position Surface form Disambiguated ID Type / Status
Subject Nynorsk E92855 entity
Predicate developedFrom P1245 FINISHED
Object Landsmål
Landsmål is the historical Norwegian written standard created in the 19th century from rural dialects, which later evolved into what is now known as Nynorsk.
 E394805 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: Landsmål | Statement: [Nynorsk, developedFrom, Landsmål]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Landsmål
Context triple: [Nynorsk, developedFrom, Landsmål]
  • A. The Fjording
    The Fjording is a Norwegian-themed gift shop in Epcot’s Norway Pavilion at Walt Disney World, offering Scandinavian merchandise such as apparel, trolls, and other cultural souvenirs.
  • B. Märsta
    Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
  • C. Lågen
    Lågen is a major river in southeastern Norway that flows through the Gudbrandsdalen valley before joining the Mjøsa lake.
  • D. Løten
    Løten is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and historic connections to painter Edvard Munch.
  • E. Maalla
    Maalla is a district of the port city of Aden in Yemen, historically significant as part of the former British-controlled Colony of Aden.
  • 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: Landsmål
Triple: [Nynorsk, developedFrom, Landsmål]
Generated description
Landsmål is the historical Norwegian written standard created in the 19th century from rural dialects, which later evolved into what is now known as Nynorsk.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Landsmål
Target entity description: Landsmål is the historical Norwegian written standard created in the 19th century from rural dialects, which later evolved into what is now known as Nynorsk.
  • A. The Fjording
    The Fjording is a Norwegian-themed gift shop in Epcot’s Norway Pavilion at Walt Disney World, offering Scandinavian merchandise such as apparel, trolls, and other cultural souvenirs.
  • B. Märsta
    Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
  • C. Lågen
    Lågen is a major river in southeastern Norway that flows through the Gudbrandsdalen valley before joining the Mjøsa lake.
  • D. Løten
    Løten is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and historic connections to painter Edvard Munch.
  • E. Maalla
    Maalla is a district of the port city of Aden in Yemen, historically significant as part of the former British-controlled Colony of Aden.
  • 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.