Triple

T16437255
Position Surface form Disambiguated ID Type / Status
Subject Flesh & Blood E399208 entity
Predicate producer P490 FINISHED
Object Michael McIntyre E1214252 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: Michael McIntyre | Statement: [Flesh & Blood, producer, Michael McIntyre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael McIntyre
Context triple: [Flesh & Blood, producer, Michael McIntyre]
  • A. Michael McIntyre chosen
    Michael McIntyre is a music producer best known for his work on the Whitesnake album "Good to Be Bad."
  • B. Michael McIntyre
    Michael McIntyre is a British stand-up comedian and television presenter known for his high-energy observational comedy and popular arena tours.
  • C. Russell Howard
    Russell Howard is a distinguished solar physicist recognized for his significant contributions to understanding the Sun and space weather.
  • D. Russell Howard
    Russell Howard is a British stand-up comedian and television presenter best known for his energetic observational comedy and shows like "Russell Howard's Good News" and "The Russell Howard Hour."
  • E. Garry McDonald
    Garry McDonald is an Australian actor and comedian best known for his satirical television character Norman Gunston and his work in film and TV drama.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba49f3481908e7ea62467ef5813 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0058143cb88190943b951cc8e47a66 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:10 a.m.