Triple

T1047263
Position Surface form Disambiguated ID Type / Status
Subject Oslo Central Station E22609 entity
Predicate servedBy P82 FINISHED
Object SJ Norge
SJ Norge is a Norwegian railway company operating passenger train services on key routes across Norway.
 E119734 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: SJ Norge | Statement: [Oslo Central Station, servedBy, SJ Norge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SJ Norge
Context triple: [Oslo Central Station, servedBy, SJ Norge]
  • A. Kongsberg
    Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
  • B. Sons of Norway
    Sons of Norway is a fraternal and cultural organization dedicated to preserving and promoting Norwegian heritage and traditions, particularly among Norwegian Americans.
  • C. Kongsvinger
    Kongsvinger is a town and municipality in Innlandet county, Norway, known for its historic fortress overlooking the Glomma River and its role as a regional center near the Swedish border.
  • D. Nilsen
    Nilsen is a surname, primarily of Scandinavian origin, that serves as a variant spelling of Nelson.
  • E. Sarpsborg
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold 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: SJ Norge
Triple: [Oslo Central Station, servedBy, SJ Norge]
Generated description
SJ Norge is a Norwegian railway company operating passenger train services on key routes across Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SJ Norge
Target entity description: SJ Norge is a Norwegian railway company operating passenger train services on key routes across Norway.
  • A. Kongsberg
    Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
  • B. Sons of Norway
    Sons of Norway is a fraternal and cultural organization dedicated to preserving and promoting Norwegian heritage and traditions, particularly among Norwegian Americans.
  • C. Kongsvinger
    Kongsvinger is a town and municipality in Innlandet county, Norway, known for its historic fortress overlooking the Glomma River and its role as a regional center near the Swedish border.
  • D. Nilsen
    Nilsen is a surname, primarily of Scandinavian origin, that serves as a variant spelling of Nelson.
  • E. Sarpsborg
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b84d30888190b66f7245d781957d completed March 1, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bcb65d08190b2ea04b6de3bb39b completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3ce6228881908f429cb0a016a17a completed March 7, 2026, 2:57 p.m.
NED2 Entity disambiguation (via description) batch_69ac3d3ed140819087ede15c555e2f4d completed March 7, 2026, 2:59 p.m.
Created at: March 1, 2026, 7:42 p.m.