Triple

T3952184
Position Surface form Disambiguated ID Type / Status
Subject David Von Ancken E84888 entity
Predicate notableWork P4 FINISHED
Object Oz E101318 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: Oz | Statement: [David Von Ancken, notableWork, Oz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oz
Context triple: [David Von Ancken, notableWork, Oz]
  • A. Oz chosen
    Oz is a gritty HBO drama series set in a maximum-security prison, known for its dark, realistic portrayal of inmate life and institutional violence.
  • B. OZ
    OZ is the IATA airline designator assigned to Asiana Airlines, a major South Korean carrier based in Seoul.
  • C. Oz, the Great and Horrible
    Oz, the Great and Horrible is the imposing yet ultimately humbug wizard who rules the Emerald City in L. Frank Baum’s classic novel "The Wonderful Wizard of Oz."
  • D. Land of Oz
    The Land of Oz is a fantastical, magical country from L. Frank Baum’s children’s book series, best known as the colorful, whimsical world visited by Dorothy and her friends.
  • E. Return to Oz
    Return to Oz is a 1985 dark fantasy film that serves as an unofficial sequel to The Wizard of Oz, blending elements from several of L. Frank Baum’s Oz books into a darker, more surreal adventure.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef939d1308190930dc2c8272eafa4 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533a80d4c8190bb1aac1b2900d9a8 completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:30 p.m.