Triple

T786483
Position Surface form Disambiguated ID Type / Status
Subject Eastern Norway E16813 entity
Predicate containsLake P1025 FINISHED
Object Mjøsa E65750 NE FINISHED

How this triple was built (2 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: Mjøsa | Statement: [Eastern Norway, containsLake, Mjøsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mjøsa
Context triple: [Eastern Norway, containsLake, Mjøsa]
  • A. Mjøsa Lake chosen
    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.
  • B. Glomma
    Glomma is Norway’s longest and largest river, flowing through Eastern Norway before emptying into the Oslofjord.
  • C. Sognefjord
    Sognefjord is Norway’s longest and deepest fjord, renowned for its dramatic cliffs, glacial landscapes, and scenic coastal villages.
  • D. Drammenselva
    Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
  • E. Oslofjord
    Oslofjord is a large inlet in southeastern Norway known for its islands, coastal towns, and role as the maritime gateway to Oslo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a77fcc6881908a025bb21e44ad56 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a93392bc448190a7920c86727c018c completed March 5, 2026, 7:41 a.m.
Created at: March 1, 2026, 7:38 p.m.