Triple

T20975166
Position Surface form Disambiguated ID Type / Status
Subject Cho Yo-han E516605 entity
Predicate notableWork P4 FINISHED
Object Columbus (2017 film) 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: Columbus (2017 film) | Statement: [Cho Yo-han, notableWork, Columbus (2017 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Columbus (2017 film)
Context triple: [Cho Yo-han, notableWork, Columbus (2017 film)]
  • A. Columbus (2017 film) chosen
    Columbus (2017 film) is a contemplative indie drama set in Columbus, Indiana, that explores architecture, family, and emotional distance through the relationship between a young woman and a man visiting his ailing father.
  • B. Columbus in Zombieland
    Columbus in Zombieland is the cautious, rule-obsessed, and socially awkward protagonist and narrator of the horror-comedy film "Zombieland."
  • C. Hancock
    Hancock is a small rural town in western Massachusetts known for its scenic Berkshire landscapes and outdoor recreation.
  • D. Hancock
    Hancock is a British television sitcom starring Tony Hancock that became a landmark of 1950s–60s UK comedy for its character-driven humor and influential writing.
  • E. Hancock
    Hancock is a small city in Michigan’s Upper Peninsula known for its Finnish-American heritage and proximity to Lake Superior.
  • 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fba307d88190b728544d1b6d0bb6 completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:46 p.m.