Triple

T6142505
Position Surface form Disambiguated ID Type / Status
Subject Trondheim E136993 entity
Predicate hasDistrict P459 FINISHED
Object Midtbyen E135247 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: Midtbyen | Statement: [Trondheim, hasDistrict, Midtbyen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Midtbyen
Context triple: [Trondheim, hasDistrict, Midtbyen]
  • A. Indre By
    Indre By is the historic city center of Copenhagen, Denmark, known for its cobblestone streets, canals, and many of the capital’s main cultural and architectural landmarks.
  • B. Midtbyen, Trondheim chosen
    Midtbyen, Trondheim is the historic city center and main downtown district of Trondheim, Norway, known for its traditional wooden architecture, commercial streets, and cultural landmarks.
  • C. St. Hanshaugen district
    St. Hanshaugen district is a central borough of Oslo, Norway, known for its large public park, historic architecture, and vibrant urban neighborhoods.
  • D. Lambertseter neighborhood
    Lambertseter neighborhood is a residential area in Oslo, Norway, known as one of the city’s first planned suburbs with significant post-war housing developments.
  • E. Lyngseidet
    Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cb387ac8190a60579b59a741425 completed March 22, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135f2defc8190a666f82e230a51c2 completed March 23, 2026, 12:45 p.m.
Created at: March 22, 2026, 4:16 p.m.