Triple

T20051624
Position Surface form Disambiguated ID Type / Status
Subject Warner Baxter E499213 entity
Predicate name P16 FINISHED
Object Warner Baxter NE NERFINISHED

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: Warner Baxter | Statement: [Warner Baxter, name, Warner Baxter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warner Baxter
Context triple: [Warner Baxter, name, Warner Baxter]
  • A. Warner Baxter chosen
    Warner Baxter was an American film actor best known for his Academy Award–winning performance in the 1928 film "In Old Arizona" and for his roles in early sound-era Hollywood dramas and crime films.
  • B. Harry Davenport
    Harry Davenport was an American character actor best known for his numerous supporting roles in classic Hollywood films of the 1930s and 1940s.
  • C. Warren William
    Warren William was an American stage and film actor of the 1930s, best known for his suave, often morally ambiguous leading and supporting roles in Hollywood pre-Code dramas and mysteries.
  • D. Charles Ruggles
    Charles Ruggles was an American character actor known for his comedic roles in film, radio, and television from the 1920s through the 1960s.
  • E. Warner Oland
    Warner Oland was a Swedish-American actor best known for portraying the detective Charlie Chan in a popular series of 1930s films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6632ee4d48190b9de3a1efa064492 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:38 p.m.