Triple

T3506360
Position Surface form Disambiguated ID Type / Status
Subject Sognefjord E74083 entity
Predicate hasTownOnShore P969 FINISHED
Object Kaupanger
Kaupanger is a village in Vestland county, Norway, known for its historic stave church and its location along the inner Sognefjord.
 E363658 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: Kaupanger | Statement: [Sognefjord, hasTownOnShore, Kaupanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kaupanger
Context triple: [Sognefjord, hasTownOnShore, Kaupanger]
  • A. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • B. Dombås
    Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
  • C. Harstad
    Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
  • D. Ballstad
    Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
  • E. Larvik
    Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
  • 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: Kaupanger
Triple: [Sognefjord, hasTownOnShore, Kaupanger]
Generated description
Kaupanger is a village in Vestland county, Norway, known for its historic stave church and its location along the inner Sognefjord.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kaupanger
Target entity description: Kaupanger is a village in Vestland county, Norway, known for its historic stave church and its location along the inner Sognefjord.
  • A. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • B. Dombås
    Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
  • C. Harstad
    Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
  • D. Ballstad
    Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
  • E. Larvik
    Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbf52bd8819085a2ac5f48cc5c68 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373e0dc7881909af631182970d132 completed March 13, 2026, 2:18 a.m.
NEDg Description generation batch_69b375337e6c8190a3d2a1561c133ecb completed March 13, 2026, 2:23 a.m.
NED2 Entity disambiguation (via description) batch_69b375bb3f8c819097b295a2881b3b82 completed March 13, 2026, 2:26 a.m.
Created at: March 8, 2026, 3:18 p.m.