Triple

T22437223
Position Surface form Disambiguated ID Type / Status
Subject Erik Axelsson Tott E554657 entity
Predicate patronymicName P7966 FINISHED
Object Axelsson NE NERFINISHED

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: Axelsson | Statement: [Erik Axelsson Tott, patronymicName, Axelsson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Axelsson
Context triple: [Erik Axelsson Tott, patronymicName, Axelsson]
  • A. Axelsson chosen
    Axelsson is a common Swedish surname borne by various notable individuals in fields such as literature, sports, and politics.
  • B. Axel Nyström
    Axel Nyström was a 19th-century Swedish architect known for his significant contributions to public and institutional architecture in Sweden.
  • C. Åkeslund
    Åkeslund is a residential district in the Bromma borough of western Stockholm, Sweden, known for its suburban character and green surroundings.
  • D. Axel Prahl
    Axel Prahl is a German actor and musician best known for his long-running role as Inspector Frank Thiel in the Münster episodes of the crime series "Tatort."
  • E. Axel
    Axel is a child associated with Nairobi, a character from the Spanish television series "Money Heist" (La Casa de Papel).
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15adf52f08190a5b592be3e68af0f completed April 29, 2026, 1:11 a.m.
Created at: April 16, 2026, 8:47 p.m.