Triple

T10354874
Position Surface form Disambiguated ID Type / Status
Subject Days of Wine and Roses E243975 entity
Predicate basedOnWorkAuthor P2806 FINISHED
Object JP Miller E857975 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: JP Miller | Statement: [Days of Wine and Roses, basedOnWorkAuthor, JP Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JP Miller
Context triple: [Days of Wine and Roses, basedOnWorkAuthor, JP Miller]
  • A. JP Miller chosen
    JP Miller was an American screenwriter and playwright best known for his hard-hitting television dramas and the film adaptation of "Days of Wine and Roses."
  • B. Carl Miller
    Carl Miller was an American silent film actor active in the 1920s, known for his supporting roles in several notable early Hollywood productions.
  • C. Sidney Miller
    Sidney Miller was a person significant enough in the history or founding of Millerton, New York, that the village was named in his honor.
  • D. Dan Miller
    Dan Miller is an American singer best known as a member of the early 2000s boy band O-Town formed on the reality TV show "Making the Band."
  • E. Robert Lane Miller
    Robert Lane Miller is an American author and legal expert known for his work on international business law and cross-border transactions.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e953d4888190b7ca0ac932349dbf completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d79529208c81909b39e3ba937c541f completed April 9, 2026, 12:01 p.m.
Created at: April 6, 2026, 11:58 a.m.