Triple

T14665800
Position Surface form Disambiguated ID Type / Status
Subject Stuart Markowitz E344368 entity
Predicate portrayedBy P1507 FINISHED
Object Michael Tucker E738294 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 Tucker | Statement: [Stuart Markowitz, portrayedBy, Michael Tucker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Tucker
Context triple: [Stuart Markowitz, portrayedBy, Michael Tucker]
  • A. Michael Tucker
    Michael Tucker, better known by his stage name BloodPop, is an American musician and record producer recognized for his work on numerous pop hits.
  • B. Michael Tucker chosen
    Michael Tucker is an American actor best known for his work in film, television, and theater, including roles in projects like the Woody Allen film "Radio Days" and the TV series "L.A. Law."
  • C. Kevin Mullen
    Kevin Mullen is a personal name shared by multiple individuals, including professionals in fields such as sports, academia, and public service.
  • D. Mark Tucker
    Mark Tucker is a video game designer known for his work on Bethesda's online action role-playing game Fallout 76.
  • E. Michael Rogers
    Michael Rogers is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts, rather than referring to one singular widely recognized figure.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54c69f8819080a37161deecfba8 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cdc54a881909d9ea43c26b9d5ef completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:27 a.m.