Triple

T8404755
Position Surface form Disambiguated ID Type / Status
Subject Anna E198466 entity
Predicate family P566 FINISHED
Object King Agnarr E677919 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: King Agnarr | Statement: [Anna, family, King Agnarr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: King Agnarr
Context triple: [Anna, family, King Agnarr]
  • A. King Agnarr chosen
    King Agnarr is the fictional monarch of Arendelle and father of Elsa and Anna in Disney's Frozen franchise.
  • B. Magnus the Good
    Magnus the Good was an 11th-century king of Norway and Denmark known for briefly uniting the two kingdoms and restoring stability after a period of dynastic conflict.
  • C. Olaf Tryggvason
    Olaf Tryggvason was a late 10th-century king of Norway known for his aggressive efforts to Christianize the country and his dramatic death at the Battle of Svolder.
  • D. Gorm the Old
    Gorm the Old was a 10th-century king of Denmark, traditionally regarded as the first historically recognized Danish monarch and the founder of the Danish royal dynasty.
  • E. Hakon Jarl
    Hakon Jarl is a dramatic work by Danish poet and playwright Adam Oehlenschläger that draws on Norse history and legend surrounding the powerful earl of Lade in Viking-age Norway.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83116bf48190894bd5d5465520ef completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02f8596c8190a61b6f1ffd5a609c completed April 2, 2026, 5:47 a.m.
Created at: March 30, 2026, 6:05 p.m.