Triple

T1138623
Position Surface form Disambiguated ID Type / Status
Subject Oslo Metro E23196 entity
Predicate terminus P388 FINISHED
Object Sognsvann
Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
E144503 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: Sognsvann | Statement: [Oslo Metro, terminus, Sognsvann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sognsvann
Context triple: [Oslo Metro, terminus, Sognsvann]
  • A. Sjusjøen
    Sjusjøen is a popular Norwegian cross-country skiing destination and mountain village known for its extensive trail network and scenic highland landscapes near Lillehammer.
  • B. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • C. Namdalen
    Namdalen is a traditional district and valley region in central Norway, known for its rivers, forests, and coastal landscapes within the county of Trøndelag.
  • D. Mjøsa Lake
    Mjøsa Lake is Norway’s largest lake, located in the southeastern part of the country and known for its scenic surroundings and historic towns along its shores.
  • E. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • 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: Sognsvann
Triple: [Oslo Metro, terminus, Sognsvann]
Generated description
Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sognsvann
Target entity description: Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • A. Sjusjøen
    Sjusjøen is a popular Norwegian cross-country skiing destination and mountain village known for its extensive trail network and scenic highland landscapes near Lillehammer.
  • B. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • C. Namdalen
    Namdalen is a traditional district and valley region in central Norway, known for its rivers, forests, and coastal landscapes within the county of Trøndelag.
  • D. Mjøsa Lake
    Mjøsa Lake is Norway’s largest lake, located in the southeastern part of the country and known for its scenic surroundings and historic towns along its shores.
  • E. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc25dda481909a26d726fdbdbb50 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99730c408190a705ca67a6724778 completed March 7, 2026, 9:32 p.m.
NEDg Description generation batch_69ac9a13e9548190ae1fbfeba3326cd5 completed March 7, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac9a96d4f081908e608a3f247bbfb2 completed March 7, 2026, 9:37 p.m.
Created at: March 1, 2026, 7:44 p.m.