Triple

T13798208
Position Surface form Disambiguated ID Type / Status
Subject Hamar Cathedral E331570 entity
Predicate locatedBy P2409 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: [Hamar Cathedral, locatedBy, Mjøsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mjøsa
Context triple: [Hamar Cathedral, locatedBy, 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. Øymarksjøen
    Øymarksjøen is a lake in southeastern Norway known for its forested surroundings, recreational fishing, and role in the local waterway system near the Swedish border.
  • C. Maridalsvannet
    Maridalsvannet is the largest lake supplying drinking water to Oslo, Norway, and a popular nearby recreation area.
  • D. Heddalsvatnet
    Heddalsvatnet is a lake in Telemark, Norway, known as part of the Telemark waterway system and surrounded by forested hills and rural landscapes.
  • 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.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8da594c81908cb878a8cc1b3a72 completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 10:11 p.m.