Triple

T8309558
Position Surface form Disambiguated ID Type / Status
Subject Nøtterøy E194555 entity
Predicate neighboringCity P988 FINISHED
Object Tønsberg E112118 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: Tønsberg | Statement: [Nøtterøy, neighboringCity, Tønsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tønsberg
Context triple: [Nøtterøy, neighboringCity, Tønsberg]
  • A. 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.
  • B. Sölvesborg
    Sölvesborg is a coastal town in southern Sweden known for its medieval architecture, historic town center, and location on the Baltic Sea in Blekinge County.
  • C. Thisted
    Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
  • D. Sønderborg
    Sønderborg is a coastal town in southern Denmark known for its historic castle, waterfront setting on the island of Als, and role as a regional cultural and educational center.
  • E. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2d2c30819095075940479b75a7 completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd05abe248190a2dc2dbb27255a87 completed April 3, 2026, 2:36 p.m.
Created at: March 30, 2026, 5:54 p.m.