Triple

T16988711
Position Surface form Disambiguated ID Type / Status
Subject Stephen Wallem E412136 entity
Predicate name P16 FINISHED
Object Stephen Wallem E412136 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: Stephen Wallem | Statement: [Stephen Wallem, name, Stephen Wallem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stephen Wallem
Context triple: [Stephen Wallem, name, Stephen Wallem]
  • A. Stephen Wallem chosen
    Stephen Wallem is an American actor and singer best known for his role as Thor Lundgren on the television series "Nurse Jackie."
  • B. Edward Lewis Wallant
    Edward Lewis Wallant was an American novelist best known for his powerful explorations of postwar Jewish-American life, most notably in the novel "The Pawnbroker."
  • C. Philip Voss
    Philip Voss was a British actor known for his extensive work in theatre, television, and radio, including roles with the Royal Shakespeare Company and appearances in popular UK dramas.
  • D. Michael Feuerstack
    Michael Feuerstack is a Canadian singer-songwriter and guitarist known for his introspective indie rock and folk music, including work under the moniker Snailhouse.
  • E. Michael Weller
    Michael Weller is an American playwright and screenwriter best known for his work on stage and film in the 1970s and 1980s, including the screenplay for the movie adaptation of the musical "Hair."
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d27dca248190a9b73b16439d5631 completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc12e308819093e7f8933cdd6ba9 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.