Triple

T5916347
Position Surface form Disambiguated ID Type / Status
Subject Adolph Tidemand E131589 entity
Predicate placeOfDeath P21 FINISHED
Object Christiania, Norway
Christiania, Norway was the former name of Oslo, the capital and largest city of Norway.
E557412 NE FINISHED

How this triple was built (4 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, placeOfDeath, Christiania, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christiania, Norway
Context triple: [Adolph Tidemand, placeOfDeath, Christiania, Norway]
  • A. 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.
  • B. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • C. Folkestad, Norway
    Folkestad, Norway is a small village in Norway historically notable as the birthplace of King Haakon IV.
  • D. 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.
  • E. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Christiania, Norway
Triple: [Adolph Tidemand, placeOfDeath, Christiania, Norway]
Generated description
Christiania, Norway was the former name of Oslo, the capital and largest city of Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Christiania, Norway
Target entity description: Christiania, Norway was the former name of Oslo, the capital and largest city of Norway.
  • A. 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.
  • B. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • C. Folkestad, Norway
    Folkestad, Norway is a small village in Norway historically notable as the birthplace of King Haakon IV.
  • D. 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.
  • E. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • F. None of above. chosen

Provenance (5 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_69c0c02c24cc8190a98d24f7445f59b7 completed March 23, 2026, 4:23 a.m.
NEDg Description generation batch_69c0c19665b08190ab3c66b7c6c33f61 completed March 23, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69c0c4576824819080ced71df8fdda6c completed March 23, 2026, 4:40 a.m.
Created at: March 22, 2026, 3:59 p.m.