Triple

T15077156
Position Surface form Disambiguated ID Type / Status
Subject Straume E380033 entity
Predicate hasShoppingCentre P4285 FINISHED
Object Straume Senter
Straume Senter is a major regional shopping mall in Straume, Norway, featuring a wide range of retail stores, services, and dining options.
 E1136039 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: Straume Senter | Statement: [Straume, hasShoppingCentre, Straume Senter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Straume Senter
Context triple: [Straume, hasShoppingCentre, Straume Senter]
  • A. Storlien
    Storlien is a village and ski resort in central Sweden near the Norwegian border, known for its winter sports and cross-border rail connections.
  • B. Sæbø
    Sæbø is a small Norwegian village known for its scenic location amid steep mountains and fjord landscapes in western Norway.
  • C. Troldhaugen
    Troldhaugen is the former home and now museum of Norwegian composer Edvard Grieg, located near Bergen and preserved as a major cultural heritage site.
  • D. Sentrum
    Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
  • E. Skedsmo
    Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
  • 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: Straume Senter
Triple: [Straume, hasShoppingCentre, Straume Senter]
Generated description
Straume Senter is a major regional shopping mall in Straume, Norway, featuring a wide range of retail stores, services, and dining options.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Straume Senter
Target entity description: Straume Senter is a major regional shopping mall in Straume, Norway, featuring a wide range of retail stores, services, and dining options.
  • A. Storlien
    Storlien is a village and ski resort in central Sweden near the Norwegian border, known for its winter sports and cross-border rail connections.
  • B. Sæbø
    Sæbø is a small Norwegian village known for its scenic location amid steep mountains and fjord landscapes in western Norway.
  • C. Troldhaugen
    Troldhaugen is the former home and now museum of Norwegian composer Edvard Grieg, located near Bergen and preserved as a major cultural heritage site.
  • D. Sentrum
    Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
  • E. Skedsmo
    Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dff7fe5a208190823900b25e298dab completed April 15, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fea5d2765481908f101bef483ed02f completed May 9, 2026, 3:11 a.m.
NEDg Description generation batch_69fea6a27c608190b1bd64c6ed90d268 completed May 9, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_69feaa8e608881909e9a7f4295e13d31 completed May 9, 2026, 3:31 a.m.
Created at: April 10, 2026, 3:03 a.m.