Triple

T1007888
Position Surface form Disambiguated ID Type / Status
Subject Jacob Bjerknes E21754 entity
Predicate placeOfBirth P1 FINISHED
Object Stockholm E14550 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: Stockholm | Statement: [Jacob Bjerknes, placeOfBirth, Stockholm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stockholm
Context triple: [Jacob Bjerknes, placeOfBirth, Stockholm]
  • A. Stockholm
    Stockholm is a fictional character in the Spanish television series "Money Heist" (La Casa de Papel), known for evolving from a hostage to a member of the heist crew.
  • B. Stockholm chosen
    Stockholm is the capital city of Sweden, renowned for its historic architecture, cultural institutions, and role as a major political, economic, and scientific center in Scandinavia.
  • C. Gothenburg
    Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
  • D. Uppsala
    Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
  • E. Old Town, Stockholm
    Old Town, Stockholm is the historic medieval center of Sweden’s capital, known for its cobblestone streets, colorful buildings, and major institutions like the Swedish Academy and the Royal Palace.
  • 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_69a493c53e648190ae8cb76c433fd9a7 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7a2186c819081a495bc15f8c7fd completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3b99a6c08190995ece1c1e9a54c9 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:41 p.m.