Triple

T8656615
Position Surface form Disambiguated ID Type / Status
Subject Torgny Lindgren E205435 entity
Predicate name P16 FINISHED
Object Torgny Lindgren E205435 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: Torgny Lindgren | Statement: [Torgny Lindgren, name, Torgny Lindgren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torgny Lindgren
Context triple: [Torgny Lindgren, name, Torgny Lindgren]
  • A. Torgny Lindgren chosen
    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.
  • B. 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.
  • 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. Sixten Jernberg
    Sixten Jernberg was a legendary Swedish cross-country skier renowned for winning multiple Olympic and World Championship medals during the 1950s and 1960s.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc484569788190aa41395854684e6f completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf285de8c081908abca2189f206a40 completed April 3, 2026, 2:39 a.m.
Created at: March 30, 2026, 6:30 p.m.