Triple

T11049817
Position Surface form Disambiguated ID Type / Status
Subject Come to Daddy E261215 entity
Predicate starring P1507 FINISHED
Object Michael Smiley E204333 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 Smiley | Statement: [Come to Daddy, starring, Michael Smiley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Smiley
Context triple: [Come to Daddy, starring, Michael Smiley]
  • A. Michael Smiley chosen
    Michael Smiley is a Northern Irish actor and comedian known for his character roles in British television and film, including notable appearances in series like Luther and Black Books.
  • B. Carl Smith
    Carl Smith was an American country music singer and guitarist prominent in the 1950s, known for hits like "Hey Joe" and for his influential honky-tonk style.
  • C. Phil Smith
    Phil Smith was an American professional basketball player best known as a two-time NBA All-Star guard and key contributor to the Golden State Warriors’ 1975 championship team.
  • D. Mel Smith
    Mel Smith was a British comedian, actor, and director best known for his work on the sketch show "Not the Nine O'Clock News" and for directing popular films such as "Bean."
  • E. Thorne Smith
    Thorne Smith was an American author best known for his humorous and risqué fantasy novels that often blended the supernatural with satirical takes on modern life.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79868c78881908c8e3672c05ae7ec completed April 9, 2026, 12:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3aa06bae08190a0db615a258ded29 completed April 18, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:26 p.m.