Triple

T10812550
Position Surface form Disambiguated ID Type / Status
Subject A Day at the Races E255137 entity
Predicate screenplayBy P15305 FINISHED
Object George Seaton E236328 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 Seaton | Statement: [A Day at the Races, screenplayBy, George Seaton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Seaton
Context triple: [A Day at the Races, screenplayBy, George Seaton]
  • A. George Seaton chosen
    George Seaton was an American screenwriter, director, and producer best known for films such as "Miracle on 34th Street" and "Airport."
  • B. Thomas Mayne
    Thomas Mayne was an Australian food scientist best known for creating the chocolate malted milk drink Milo in the 1930s.
  • C. John Seaton
    John Seaton is a fictional character from the 1978 British-American sports drama film "International Velvet."
  • D. Walter Boyd
    Walter Boyd is a former Jamaican international footballer best known for his prolific goal-scoring and charismatic playing style as a forward in the 1990s and early 2000s.
  • E. Joseph McHardy
    Joseph McHardy is a musician and choral director known for his work with prominent British church and cathedral choirs.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733eadda48190b2b1183ee60102cb completed April 9, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23b7578688190975c087d28808be5 completed April 17, 2026, 1:53 p.m.
Created at: April 8, 2026, 9:18 p.m.