Triple

T16331353
Position Surface form Disambiguated ID Type / Status
Subject Crashing Towers E396559 entity
Predicate featuresActor P15562 FINISHED
Object George Sowards E493398 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: George Sowards | Statement: [Crashing Towers, featuresActor, George Sowards]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Sowards
Context triple: [Crashing Towers, featuresActor, George Sowards]
  • A. George Sowards chosen
    George Sowards is an actor known for his role in the film "Shotgun."
  • B. David Holbrook
    David Holbrook is a British literary critic and scholar known for his work on modernist literature, education, and cultural criticism.
  • C. Dylan Baker
    Dylan Baker is an American character actor known for his versatile roles in film, television, and theater, including appearances in movies like "Planes, Trains and Automobiles" and the "Spider-Man" series.
  • D. Shea Whigham
    Shea Whigham is an American character actor known for his intense, often gritty supporting roles in film and television, including prominent parts in series like "Boardwalk Empire" and numerous acclaimed movies.
  • E. Timothy Busfield
    Timothy Busfield is an American actor and director best known for his roles in television series such as "thirtysomething," "The West Wing," and various film and stage productions.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4dfd9688190a749e48ebc055baf completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00580d372c81908fcc267cdc3812a7 completed May 10, 2026, 10:03 a.m.
Created at: April 10, 2026, 5:07 a.m.