Triple

T3517884
Position Surface form Disambiguated ID Type / Status
Subject Stavanger E74350 entity
Predicate near P350 FINISHED
Object Preikestolen
Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
 E365816 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: Preikestolen | Statement: [Stavanger, near, Preikestolen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Preikestolen
Context triple: [Stavanger, near, Preikestolen]
  • A. Galdhøpiggen
    Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
  • B. Higravstinden
    Higravstinden is a prominent mountain peak in Norway’s Lofoten archipelago, known for its rugged alpine terrain and striking coastal views.
  • C. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • D. Es Migjorn Gran
    Es Migjorn Gran is a small, rural municipality and village located in the southern part of the Balearic Island of Menorca, Spain.
  • E. Skøyen
    Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
  • 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: Preikestolen
Triple: [Stavanger, near, Preikestolen]
Generated description
Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Preikestolen
Target entity description: Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
  • A. Galdhøpiggen
    Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
  • B. Higravstinden
    Higravstinden is a prominent mountain peak in Norway’s Lofoten archipelago, known for its rugged alpine terrain and striking coastal views.
  • C. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • D. Es Migjorn Gran
    Es Migjorn Gran is a small, rural municipality and village located in the southern part of the Balearic Island of Menorca, Spain.
  • E. Flåm
    Flåm is a small Norwegian village in Aurland municipality, best known for its dramatic fjord scenery and the scenic Flåm Railway that attracts many tourists.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc32f90081908960acb3e94402be completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e80cd588190ae012f151ef59c52 completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37ef902208190842ddbe6427ca42b completed March 13, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_69b382b43b708190be7ae3d44b0a393a completed March 13, 2026, 3:21 a.m.
Created at: March 8, 2026, 3:19 p.m.