Triple

T9015647
Position Surface form Disambiguated ID Type / Status
Subject The Cutting Edge E215586 entity
Predicate mainCharacter P1183 FINISHED
Object Kate Moseley E721887 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: Kate Moseley | Statement: [The Cutting Edge, mainCharacter, Kate Moseley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Moseley
Context triple: [The Cutting Edge, mainCharacter, Kate Moseley]
  • A. Kate Moseley chosen
    Kate Moseley is the driven, once-elite figure skater character from the romantic sports film "The Cutting Edge."
  • B. Jennifer Mordaunt
    Jennifer Mordaunt is a relative of British Conservative politician Penny Mordaunt.
  • C. Alison Ellwood
    Alison Ellwood is an American documentary film editor and director known for her work on acclaimed non-fiction films and series.
  • D. Victoria Prentis
    Victoria Prentis is a British Conservative Party politician and government minister who has served as the Member of Parliament for Banbury since 2015.
  • E. Rachel Treweek
    Rachel Treweek is a British Anglican bishop notable for being the first woman to serve as a diocesan bishop in the Church of England and the first female bishop to sit in the House of Lords.
  • 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_69ca83a38aa88190bf1bb80c4548b5e2 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69fc0e4c819080b60456375f94cd completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb7117c48190a9dca7bbdabe9e3d completed April 3, 2026, 4:31 p.m.
Created at: March 30, 2026, 7:06 p.m.