Triple

T1561009
Position Surface form Disambiguated ID Type / Status
Subject Oslofjord E33322 entity
Predicate adjacentToCity P5707 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: [Oslofjord, adjacentToCity, Tønsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tønsberg
Context triple: [Oslofjord, adjacentToCity, 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. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • C. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • D. Sandefjord
    Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
  • E. Kolding
    Kolding is a historic Danish city in Southern Jutland known for Koldinghus Castle, its fjord-side location, and its role as a regional cultural and educational 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9088710a881909a1226e4b54311b8 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3b2c2788190a22c3b45dedb1484 completed March 8, 2026, 10:09 p.m.
Created at: March 4, 2026, 7:27 p.m.