Triple

T4446438
Position Surface form Disambiguated ID Type / Status
Subject Valdres E96299 entity
Predicate hasLake P1025 FINISHED
Object Vangsmjøse
Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
E442491 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: Vangsmjøse | Statement: [Valdres, hasLake, Vangsmjøse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vangsmjøse
Context triple: [Valdres, hasLake, Vangsmjøse]
  • 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. Ranfjorden
    Ranfjorden is a long, narrow fjord in Nordland county, Norway, known for its dramatic coastal landscape and the industrial town of Mo i Rana along its shores.
  • C. Målselva
    Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
  • D. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • E. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • 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: Vangsmjøse
Triple: [Valdres, hasLake, Vangsmjøse]
Generated description
Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vangsmjøse
Target entity description: Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
  • 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. Ranfjorden
    Ranfjorden is a long, narrow fjord in Nordland county, Norway, known for its dramatic coastal landscape and the industrial town of Mo i Rana along its shores.
  • C. Målselva
    Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
  • D. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • E. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d1eba08190899d0a3c1684ce4e completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b62818295481909c0ffa377570effc completed March 15, 2026, 3:31 a.m.
NEDg Description generation batch_69b628ffed1c819097d048712e9aafef completed March 15, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69b6298d1ff88190a58a6fc5992ef864 completed March 15, 2026, 3:37 a.m.
Created at: March 12, 2026, 11:32 p.m.