Triple

T21117527
Position Surface form Disambiguated ID Type / Status
Subject My Name Is Emily E520336 entity
Predicate starring P1507 FINISHED
Object Michael Smiley 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: Michael Smiley | Statement: [My Name Is Emily, starring, Michael Smiley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Smiley
Context triple: [My Name Is Emily, 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. Phil Smith
    Phil Smith was a mountaineer known for making the first recorded ascent of Middle Teton in the Teton Range of Wyoming.
  • E. 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."
  • 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_69e0b50a623881909c0bbaf4f2c055e7 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e721078ac48190980441b6ada0e2b4 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:55 p.m.