Triple

T16263200
Position Surface form Disambiguated ID Type / Status
Subject Christian Magnus Falsen E394806 entity
Predicate placeOfBirth P1 FINISHED
Object Christiania E153896 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 | Statement: [Christian Magnus Falsen, placeOfBirth, Christiania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christiania
Context triple: [Christian Magnus Falsen, placeOfBirth, Christiania]
  • A. Christiania chosen
    Christiania is the former name of Norway’s capital city, Oslo, used from the 17th century until the early 20th century.
  • B. Freetown Christiania
    Freetown Christiania is a semi-autonomous, alternative community and cultural district in Copenhagen known for its countercultural lifestyle, art, and unique self-governance.
  • C. Inner City of Copenhagen
    The Inner City of Copenhagen is the historic and commercial heart of Denmark’s capital, known for its medieval street layout, iconic landmarks, and dense mix of cultural, political, and shopping districts.
  • D. Tjuvholmen
    Tjuvholmen is a modern waterfront district in central Oslo known for its contemporary architecture, art galleries, and seaside promenade.
  • E. Sydhavn
    Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c5583c8190901e892238cf8dbd completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b5f3a8819083128cf2b90cfd84 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:04 a.m.