Triple

T14358694
Position Surface form Disambiguated ID Type / Status
Subject Sleeper Cell E356038 entity
Predicate castMember P1668 FINISHED
Object James LeGros E452906 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: James LeGros | Statement: [Sleeper Cell, castMember, James LeGros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: James LeGros
Context triple: [Sleeper Cell, castMember, James LeGros]
  • A. James LeGros chosen
    James LeGros is an American character actor known for his work in independent films and television, including roles in projects like "Drugstore Cowboy," "Ally McBeal," and "Justified."
  • B. Michael LeSieur
    Michael LeSieur is an American screenwriter known for his work on comedy films, including co-writing the 2018 animated adaptation of Dr. Seuss's "The Grinch."
  • C. James Lesure
    James Lesure is an American television actor known for his roles in series such as Las Vegas, For Your Love, and Good Girls.
  • D. Charles LeMaire
    Charles LeMaire was an American costume designer renowned for his work in Hollywood’s Golden Age, earning multiple Academy Awards for his contributions to classic films.
  • E. Kevin Grevioux
    Kevin Grevioux is an American actor, screenwriter, and comic book writer best known for co-creating the dark fantasy film franchise "Underworld."
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f52ca7881908704eef20228aed3 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7ed3ec8190b97128733419845b completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:15 a.m.