Triple

T22091427
Position Surface form Disambiguated ID Type / Status
Subject I'd Do Anything E545922 entity
Predicate presenter P83 FINISHED
Object Graham Norton 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: Graham Norton | Statement: [I'd Do Anything, presenter, Graham Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graham Norton
Context triple: [I'd Do Anything, presenter, Graham Norton]
  • A. Graham Norton chosen
    Graham Norton is an Irish television and radio presenter, comedian, and actor best known for hosting the long-running BBC chat show "The Graham Norton Show."
  • B. Paul Merton
    Paul Merton is a British comedian and improviser best known for his long-running appearances on radio and television panel shows such as "Have I Got News for You" and "Just a Minute."
  • C. Michael McIntyre
    Michael McIntyre is a music producer best known for his work on the Whitesnake album "Good to Be Bad."
  • D. Michael McIntyre
    Michael McIntyre is a British stand-up comedian and television presenter known for his high-energy observational comedy and popular arena tours.
  • E. Russell Howard
    Russell Howard is a distinguished solar physicist recognized for his significant contributions to understanding the Sun and space weather.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e5edf08190a6743955bc872417 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.