Triple

T8326421
Position Surface form Disambiguated ID Type / Status
Subject The Story of Sigurd the Volsung and the Fall of the Niblungs E194964 entity
Predicate mainCharacter P1183 FINISHED
Object Gunnar E30461 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: Gunnar | Statement: [The Story of Sigurd the Volsung and the Fall of the Niblungs, mainCharacter, Gunnar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gunnar
Context triple: [The Story of Sigurd the Volsung and the Fall of the Niblungs, mainCharacter, 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. Gunnar Fant
    Gunnar Fant was a pioneering Swedish speech scientist and phonetician renowned for his foundational work on the acoustic theory of speech production.
  • D. Egil
    Egil is a masculine given name of Old Norse origin, traditionally used in Scandinavian countries.
  • E. Ragnar
    Ragnar is a masculine given name of Old Norse origin, historically associated with Viking-age Scandinavia and later borne by various notable figures.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f7fba688190b696593dfb2cde5d completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95b92708819097795498f9ebcdfc completed April 1, 2026, 10:01 p.m.
Created at: March 30, 2026, 5:56 p.m.