Triple

T1920135
Position Surface form Disambiguated ID Type / Status
Subject Wonderful Town E40106 entity
Predicate lyricist P1360 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: [Wonderful Town, lyricist, Adolph Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adolph Green
Context triple: [Wonderful Town, lyricist, 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. Charles Bickford
    Charles Bickford was an American character actor known for his rugged screen presence and acclaimed supporting roles in numerous classic Hollywood films.
  • C. Eddie Albert
    Eddie Albert was an American actor best known for his roles in film and television, particularly the sitcom "Green Acres" and numerous classic Hollywood movies.
  • D. Roy Harlow
    Roy Harlow was the husband of silent film actress Marie Mosquini, known primarily in relation to her career in early American cinema.
  • E. Warner Oland
    Warner Oland was a Swedish-American actor best known for portraying the detective Charlie Chan in a popular series of 1930s 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb213af0481909429ec971860a3fd completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3042bdf08190bf43c9246fcc114e completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:35 p.m.