Triple

T4446446
Position Surface form Disambiguated ID Type / Status
Subject Valdres E96299 entity
Predicate hasDialect P4251 FINISHED
Object Valdresmål
Valdresmål is a traditional Norwegian dialect spoken in the Valdres region, known for its distinctive phonology and preservation of many Old Norse features.
E440927 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: Valdresmål | Statement: [Valdres, hasDialect, Valdresmål]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valdresmål
Context triple: [Valdres, hasDialect, Valdresmål]
  • A. Malangen
    Malangen is a prominent fjord in northern Norway known for its scenic coastal landscapes and proximity to the city of Tromsø in Troms county.
  • B. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • C. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • D. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • E. Svolvær
    Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
  • 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: Valdresmål
Triple: [Valdres, hasDialect, Valdresmål]
Generated description
Valdresmål is a traditional Norwegian dialect spoken in the Valdres region, known for its distinctive phonology and preservation of many Old Norse features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Valdresmål
Target entity description: Valdresmål is a traditional Norwegian dialect spoken in the Valdres region, known for its distinctive phonology and preservation of many Old Norse features.
  • A. Malangen
    Malangen is a prominent fjord in northern Norway known for its scenic coastal landscapes and proximity to the city of Tromsø in Troms county.
  • B. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • C. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • D. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • E. Svolvær
    Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d1eba08190899d0a3c1684ce4e completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61386df48819080e44a23b9d67d23 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b617c13d4481909d22d201ce405d3a completed March 15, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_69b6187687f8819084e2d611e9e31f79 completed March 15, 2026, 2:24 a.m.
Created at: March 12, 2026, 11:32 p.m.