Triple

T3898684
Position Surface form Disambiguated ID Type / Status
Subject Come and Get It E90433 entity
Predicate screenwriter P2831 FINISHED
Object Jules Furthman E46932 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: Jules Furthman | Statement: [Come and Get It, screenwriter, Jules Furthman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jules Furthman
Context triple: [Come and Get It, screenwriter, Jules Furthman]
  • A. Jules Furthman chosen
    Jules Furthman was an American screenwriter renowned for his work on numerous classic Hollywood films from the silent era through the 1940s, including collaborations with directors like Howard Hawks.
  • B. George Marks
    George Marks was a film editor known for his work on early American cinema, including the pioneering all-talking feature "Lights of New York."
  • C. Jerry Livingston
    Jerry Livingston was an American songwriter and composer best known for his popular film and pop standards, including work on classic Disney songs.
  • D. Sammy Fain
    Sammy Fain was an American composer best known for writing popular standards and film songs, including several classic Disney and Hollywood melodies.
  • E. Milton Ager
    Milton Ager was an American songwriter and composer best known for his popular standards of the early 20th century, many of which became enduring hits of the Tin Pan Alley era.
  • 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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecefa3608190a7a20ed6df6a64b2 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5285093208190a2ba00afcbd8a261 completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:21 p.m.