Triple

T10057693
Position Surface form Disambiguated ID Type / Status
Subject Klas Östergren E208902 entity
Predicate name P16 FINISHED
Object Klas Östergren E208902 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: Klas Östergren | Statement: [Klas Östergren, name, Klas Östergren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klas Östergren
Context triple: [Klas Östergren, name, Klas Östergren]
  • A. Klas Östergren chosen
    Klas Östergren is a prominent Swedish novelist, screenwriter, and translator known for works such as "Gentlemen" and his contributions to contemporary Scandinavian literature.
  • B. Ted Gärdestad
    Ted Gärdestad was a Swedish singer-songwriter and musician known for his melodic pop songs in the 1970s and collaborations with members of ABBA.
  • C. Erik Kråkström
    Erik Kråkström was a Finnish architect known for his modernist industrial and residential designs, including significant work on the Sunila Pulp Mill complex.
  • D. Björn Waldegård
    Björn Waldegård was a Swedish rally driver and the inaugural World Rally Championship drivers’ title winner, renowned for his success with multiple manufacturers during the 1970s and 1980s.
  • E. Leif Sjöberg
    Leif Sjöberg was a Swedish translator and scholar known for bringing modern Arabic literature to Scandinavian readers.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcfaf7700819084dedf7b63e789c1 completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cba6971c819090689917cd9b5b7c completed April 5, 2026, 8:52 p.m.
Created at: March 30, 2026, 8:57 p.m.