Triple

T4568773
Position Surface form Disambiguated ID Type / Status
Subject Good Morning E121977 entity
Predicate title P38 FINISHED
Object Good Morning E121977 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: Good Morning | Statement: [Good Morning, title, Good Morning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Good Morning
Context triple: [Good Morning, title, Good Morning]
  • A. Good Morning chosen
    "Good Morning" is a classic show tune best known from the 1939 musical film *Babes in Arms* and later popularized in *Singin' in the Rain*.
  • B. Good Morning
    "Good Morning" is a vibrant abstract painting by British artist Howard Hodgkin, known for its expressive brushwork and intense, layered color.
  • C. Good Morning Love
    "Good Morning Love" is a romantic song, likely a track from the music project or album "Let Love."
  • D. Joy in the Morning
    "Joy in the Morning" is a comic novel in P. G. Wodehouse’s Jeeves and Wooster series, featuring Bertie Wooster’s misadventures and the ingenious problem-solving of his valet Jeeves.
  • E. Good Morning Good Morning
    "Good Morning Good Morning" is a 1967 Beatles song written primarily by John Lennon, notable for its brassy arrangement, shifting time signatures, and use of animal sound effects.
  • 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_69bd463f156881908a99aca69c5721ac completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58a0dfbc81909b5023f0c29addaf completed March 20, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3bf54448190a7e65cee1a5c48e3 completed March 20, 2026, 11:09 p.m.
Created at: March 20, 2026, 1:10 p.m.