Triple

T22873384
Position Surface form Disambiguated ID Type / Status
Subject Akata Witch E567257 entity
Predicate publisher P29 FINISHED
Object Viking 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: Viking | Statement: [Akata Witch, publisher, Viking]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viking
Context triple: [Akata Witch, publisher, Viking]
  • A. Viking
    "Viking" is a Russian historical epic film depicting the rise of Prince Vladimir and the Christianization of Kievan Rus.
  • B. Viking
    The Viking is a Norse seafaring warrior figure commonly used as a symbol of strength and bravery, including as a school mascot.
  • C. Viking
    Viking is a Norwegian professional football club based in Stavanger, known for competing in the country’s top division and having a rich domestic history.
  • D. Viking chosen
    Viking is a prominent American publishing imprint known for releasing influential fiction and nonfiction titles, including many literary classics and bestsellers.
  • E. Viking
    Viking is a tire brand owned by Continental AG, known for producing reliable and affordable tires for passenger cars and light commercial vehicles.
  • 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_69e24589d8348190b96422d13a678bc1 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17f55c4b88190adb49871e496ca54 completed April 29, 2026, 3:47 a.m.
Created at: April 17, 2026, 3:38 p.m.