Triple

T11279846
Position Surface form Disambiguated ID Type / Status
Subject George Raft E267034 entity
Predicate name P16 FINISHED
Object George Raft E267034 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 Raft | Statement: [George Raft, name, George Raft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Raft
Context triple: [George Raft, name, George Raft]
  • A. George Raft chosen
    George Raft was an American film actor and dancer best known for his tough-guy roles in 1930s and 1940s gangster films such as "Scarface" and "Each Dawn I Die."
  • 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. Ricardo Cortez
    Ricardo Cortez was an American actor of the silent and early sound film era, best known for his leading-man roles in crime dramas and early film noir.
  • D. Warner Oland
    Warner Oland was a Swedish-American actor best known for portraying the detective Charlie Chan in a popular series of 1930s films.
  • E. 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.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e969b3448190940e2bd499d2d7de completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f46308348190a47f73030cae0be5 completed April 19, 2026, 3:27 p.m.
Created at: April 8, 2026, 9:31 p.m.