Triple

T19403727
Position Surface form Disambiguated ID Type / Status
Subject Tønsberg harbor E485394 entity
Predicate partOf P40 FINISHED
Object Tønsberg town center NE NERFINISHED

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: Tønsberg town center | Statement: [Tønsberg harbor, partOf, Tønsberg town center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tønsberg town center
Context triple: [Tønsberg harbor, partOf, Tønsberg town center]
  • A. Tønsberg city hall
    Tønsberg city hall is the main administrative and political center of the city of Tønsberg, Norway, housing its municipal government offices and council chambers.
  • B. Tønsberg chosen
    Tønsberg is a historic coastal town in southeastern Norway, often regarded as one of the country’s oldest cities and known for its Viking heritage and maritime culture.
  • C. Kongsberg town centre
    Kongsberg town centre is the central urban area of Kongsberg, Norway, known for its historic silver mining heritage and role as the city’s commercial and cultural hub.
  • D. 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.
  • 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 (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6257937d081909dbc5804d2505938 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.