Triple

T12837681
Position Surface form Disambiguated ID Type / Status
Subject Warren Foster E306959 entity
Predicate name P16 FINISHED
Object Warren Foster E306959 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: Warren Foster | Statement: [Warren Foster, name, Warren Foster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Foster
Context triple: [Warren Foster, name, Warren Foster]
  • A. Warren Foster chosen
    Warren Foster was an American animation writer best known for his influential work on classic Warner Bros. cartoons, including many featuring characters like Foghorn Leghorn.
  • B. Leo Willis
    Leo Willis was an American character actor active during the silent and early sound film eras, often appearing in comedies alongside stars like Harold Lloyd.
  • C. 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.
  • D. William Katt
    William Katt is an American actor best known for starring in the 1980s television series "The Greatest American Hero" and appearing in films such as "Carrie."
  • E. Paul Dooley
    Paul Dooley is an American character actor, writer, and comedian known for his roles in films such as "Breaking Away," "Sixteen Candles," and numerous television series.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff015f4819090070a01f3938acc completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fefabc8081908e46ffcaef22cce1 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 5:35 p.m.