Triple

T5916365
Position Surface form Disambiguated ID Type / Status
Subject Adolph Tidemand E131589 entity
Predicate workLocation P7 FINISHED
Object Christiania, Norway E557412 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: Christiania, Norway | Statement: [Adolph Tidemand, workLocation, Christiania, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christiania, Norway
Context triple: [Adolph Tidemand, workLocation, Christiania, Norway]
  • A. Christiania, Norway chosen
    Christiania, Norway was the former name of Oslo, the capital and largest city of Norway.
  • B. Rosendal, Norway
    Rosendal, Norway is a small village in Kvinnherad municipality in Vestland county, known for its dramatic fjord landscape and the historic Barony Rosendal manor.
  • 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. Folkestad, Norway
    Folkestad, Norway is a small village in Norway historically notable as the birthplace of King Haakon IV.
  • E. Horten, Norway
    Horten, Norway is a coastal town and municipality in Vestfold known for its maritime heritage, naval history, and ferry link across the Oslofjord.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037bcea9c8190a34dc03857e3b80b completed March 22, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e397f2748190acf2d629ee57a466 completed March 23, 2026, 6:54 a.m.
Created at: March 22, 2026, 3:59 p.m.