Triple

T14657776
Position Surface form Disambiguated ID Type / Status
Subject The Mask of Zorro E344153 entity
Predicate starring P1507 FINISHED
Object Matt Letscher E962691 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: Matt Letscher | Statement: [The Mask of Zorro, starring, Matt Letscher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Letscher
Context triple: [The Mask of Zorro, starring, Matt Letscher]
  • A. Matt Letscher chosen
    Matt Letscher is an American actor known for his work in television, film, and theater, including prominent roles in series such as "The Flash," "Boardwalk Empire," and "The Carrie Diaries."
  • B. Chris Loken
    Chris Loken is the mother of American actress and model Kristanna Loken.
  • C. Cory Finley
    Cory Finley is an American filmmaker and playwright best known for his darkly comedic and psychologically driven films such as "Thoroughbreds" and "Bad Education."
  • D. Jason Berkley
    Jason Berkley is known as the brother of American actress Elizabeth Berkley, recognized for her roles in "Saved by the Bell" and "Showgirls."
  • E. Marty Mikalski
    Marty Mikalski is the paranoid, stoner college student whose unexpected insight and survival instincts play a crucial role in the horror-comedy film "The Cabin in the Woods."
  • 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_69deb51b6a248190a44050c0e0ec2d16 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5e01cd081909c71fdcf67c3b1f5 completed May 8, 2026, 12:24 p.m.
Created at: April 10, 2026, 1:27 a.m.