Triple

T8867209
Position Surface form Disambiguated ID Type / Status
Subject Claire de Loone E211047 entity
Predicate createdForWorkBy P65723 FINISHED
Object Adolph Green E71773 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: Adolph Green | Statement: [Claire de Loone, createdForWorkBy, Adolph Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adolph Green
Context triple: [Claire de Loone, createdForWorkBy, Adolph Green]
  • A. Adolph Green chosen
    Adolph Green was an American playwright, lyricist, and screenwriter best known for his long collaboration with Betty Comden on classic Broadway musicals and Hollywood films.
  • B. Otto Hunte
    Otto Hunte was a prominent German film art director and production designer best known for his influential work on classic Weimar-era films, including Fritz Lang’s Metropolis.
  • C. Lewis Allen
    Lewis Allen was a local figure of significance after whom the city of Allen Park, Michigan, was named.
  • D. Lewis Allen
    Lewis Allen was a British-born film and television director best known for his atmospheric work in mid-20th-century Hollywood cinema.
  • E. Charles Bickford
    Charles Bickford was an American character actor known for his rugged screen presence and acclaimed supporting roles in numerous classic Hollywood films.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6108530c819084559f4de669ce20 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb8094a88190a88e3f23f9ae17c7 completed April 3, 2026, 3:23 p.m.
Created at: March 30, 2026, 6:51 p.m.