Triple

T9837106
Position Surface form Disambiguated ID Type / Status
Subject Spawn of the North E239129 entity
Predicate hasCastMember P2308 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: [Spawn of the North, hasCastMember, George Raft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Raft
Context triple: [Spawn of the North, hasCastMember, 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb33b07688190b78a70cf535c3efc completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1ead061388190abbed7eb29e8ea52 completed April 5, 2026, 4:53 a.m.
Created at: March 30, 2026, 8:33 p.m.