Triple

T17764818
Position Surface form Disambiguated ID Type / Status
Subject Tony Hatch E443475 entity
Predicate notableWork P4 FINISHED
Object Round Every Corner 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: Round Every Corner | Statement: [Tony Hatch, notableWork, Round Every Corner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Round Every Corner
Context triple: [Tony Hatch, notableWork, Round Every Corner]
  • A. Round Every Corner chosen
    "Round Every Corner" is a 1965 pop song recorded by British singer Petula Clark that reflects the upbeat, optimistic style of her mid-1960s hits.
  • B. Cornershop
    Cornershop is an on-demand grocery delivery service, originally founded in Latin America, that connects users with local supermarkets and retailers through a mobile app and web platform.
  • C. Corkscrew Corners
    Corkscrew Corners is a themed area within Michigan's Adventure amusement park that features the Shivering Timbers wooden roller coaster and other attractions.
  • D. The Very Edge
    The Very Edge is a 1963 British thriller film starring Anne Heywood as a woman terrorized by a psychopathic killer.
  • E. Shooting into the Corner
    Shooting into the Corner is a large-scale installation by artist Anish Kapoor that dramatically fires red wax into a gallery corner, exploring themes of violence, materiality, and spectacle.
  • 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485fb2a3c81908887d1d36aee942d completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.