Triple

T18136199
Position Surface form Disambiguated ID Type / Status
Subject Per Gunnar Hansson E434142 entity
Predicate givenName P17 FINISHED
Object Gunnar 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: Gunnar | Statement: [Per Gunnar Hansson, givenName, Gunnar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gunnar
Context triple: [Per Gunnar Hansson, givenName, Gunnar]
  • A. Gunnar chosen
    Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
  • B. Ivar
    Ivar is a masculine given name of Old Norse origin, traditionally used in Scandinavian countries.
  • C. Eyvind
    Eyvind is a masculine given name of Old Norse origin, historically associated with Scandinavian culture and borne by figures such as the American artist Eyvind Earle.
  • D. Gunnar Fant
    Gunnar Fant was a pioneering Swedish speech scientist and phonetician renowned for his foundational work on the acoustic theory of speech production.
  • E. Gunnar Gren
    Gunnar Gren was a legendary Swedish footballer and playmaker, best known as part of the famed "Gre-No-Li" trio at AC Milan and for helping Sweden win Olympic gold in 1948 and reach the 1958 World Cup final.
  • 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de07b4b4819085fe80beb7addfd0 completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.