Triple

T15625446
Position Surface form Disambiguated ID Type / Status
Subject Scott Pilgrim vs. the World E375664 entity
Predicate cinematographyBy P1953 FINISHED
Object Bill Pope E195722 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: Bill Pope | Statement: [Scott Pilgrim vs. the World, cinematographyBy, Bill Pope]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Pope
Context triple: [Scott Pilgrim vs. the World, cinematographyBy, Bill Pope]
  • A. Bill Pope chosen
    Bill Pope is an acclaimed American cinematographer best known for his dynamic, visually inventive work on major films such as The Matrix trilogy and the Spider-Man series.
  • B. Ryan Pope
    Ryan Pope is an American drummer best known for his work with the emo and indie rock band The Get Up Kids.
  • C. Dave Pope
    Dave Pope is the husband of American actress and model Joy Bryant.
  • D. Phil Housley
    Phil Housley is an American former professional ice hockey defenseman renowned as one of the highest-scoring blueliners in NHL history and later a coach at the league level.
  • E. Bill Nunn
    Bill Nunn was a pioneering NFL scout and journalist renowned for helping transform the Pittsburgh Steelers into a dynasty by recruiting standout talent from historically Black colleges and universities.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f415c2c81909e232e1c6531da93 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.