Triple

T14734583
Position Surface form Disambiguated ID Type / Status
Subject Tvedestrand E346169 entity
Predicate hasUrbanArea P316 FINISHED
Object Tvedestrand town centre E346169 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: Tvedestrand town centre | Statement: [Tvedestrand, hasUrbanArea, Tvedestrand town centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tvedestrand town centre
Context triple: [Tvedestrand, hasUrbanArea, Tvedestrand town centre]
  • A. Tvedestrand chosen
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • B. Trondheim Torg shopping center
    Trondheim Torg shopping center is a central retail complex in downtown Trondheim, Norway, featuring a wide range of shops, dining options, and services.
  • C. Smestad
    Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
  • D. Hafjell village
    Hafjell village is a small Norwegian settlement known primarily for its proximity to the Hafjell ski resort and the Lillehammer Olympic region.
  • E. Tøyen Torg
    Tøyen Torg is a central square and commercial hub in Oslo’s Tøyen neighborhood, known for its shops, cafés, and multicultural urban atmosphere.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec72ea9348190817efcdaa973d7f7 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0ce6514c8190a37b023dcc0c1b1a completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:29 a.m.