Triple

T16485270
Position Surface form Disambiguated ID Type / Status
Subject Sixten Jernberg E400422 entity
Predicate name P16 FINISHED
Object Sixten Jernberg E400422 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: Sixten Jernberg | Statement: [Sixten Jernberg, name, Sixten Jernberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sixten Jernberg
Context triple: [Sixten Jernberg, name, Sixten Jernberg]
  • A. Sixten Jernberg chosen
    Sixten Jernberg was a legendary Swedish cross-country skier renowned for winning multiple Olympic and World Championship medals during the 1950s and 1960s.
  • B. Torgny Lindgren
    Torgny Lindgren was a renowned Swedish author and member of the Swedish Academy, celebrated for his novels and short stories often set in rural Västerbotten.
  • C. Östen Undén
    Östen Undén was a Swedish Social Democratic politician, legal scholar, and long-serving foreign minister who briefly served as acting Prime Minister of Sweden during the 1940s.
  • D. Torgny Segerstedt
    Torgny Segerstedt was a Swedish philosopher and academic leader best known for serving as rector of Uppsala University and for his influence on higher education in Sweden.
  • E. Johan Söderqvist
    Johan Söderqvist is a Swedish film composer known for his atmospheric and emotionally nuanced scores for Scandinavian and international cinema.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e05bf448190947b9da15fd29d0a completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a008a2363208190beb218e633d0627e completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 5:13 a.m.