Triple

T2985321
Position Surface form Disambiguated ID Type / Status
Subject XIV Olympiad E80610 entity
Predicate IOCPresidentDuringGames P10857 FINISHED
Object Sigfrid Edström E80998 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: Sigfrid Edström | Statement: [XIV Olympiad, IOCPresidentDuringGames, Sigfrid Edström]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sigfrid Edström
Context triple: [XIV Olympiad, IOCPresidentDuringGames, Sigfrid Edström]
  • A. Sigfrid Edström chosen
    Sigfrid Edström was a Swedish industrialist and sports administrator who served as president of the International Olympic Committee in the mid-20th century.
  • B. Johan Söderqvist
    Johan Söderqvist is a Swedish film composer known for his atmospheric and emotionally nuanced scores for Scandinavian and international cinema.
  • C. 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.
  • D. Emil Sodersten
    Emil Sodersten was a prominent Australian architect of the early 20th century, noted for his influential modernist and Art Deco designs.
  • E. Göran Månsson
    Göran Månsson is a Swedish architect best known for designing Stockholm’s renowned Vasa Museum, which houses the 17th-century warship Vasa.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c65ad0819087bb4ae92ab0dc55 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108f8b2b08190904cf89befe656dd completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:59 p.m.