Triple

T15448158
Position Surface form Disambiguated ID Type / Status
Subject Brumunddal E370077 entity
Predicate locatedNear P294 FINISHED
Object Lake 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: Lake Mjøsa | Statement: [Brumunddal, locatedNear, Lake Mjøsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Mjøsa
Context triple: [Brumunddal, locatedNear, Lake 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. Breiddalsvatnet
    Breiddalsvatnet is a lake located in Skjåk municipality in Innlandet county, Norway, known for its mountainous surroundings and role in local outdoor recreation.
  • C. Lake Norsjø
    Lake Norsjø is a large inland lake in Telemark, Norway, known as an important link in the Telemark Canal and a popular area for boating and recreation.
  • D. Rembesdalsvatnet
    Rembesdalsvatnet is a mountain lake in Ulvik municipality in Vestland county, western Norway, known for its scenic setting near the Hardangerjøkulen glacier.
  • E. Djupvatnet
    Djupvatnet is a high-altitude lake in Norway’s Møre og Romsdal county, known for its scenic mountain surroundings and proximity to popular tourist routes.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff9978ae90819088bf7c8890b7a9a5 completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 3:21 a.m.