Triple

T2116794
Position Surface form Disambiguated ID Type / Status
Subject Follow the Fleet E43826 entity
Predicate starring P1507 FINISHED
Object Lucille Ball E8857 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: Lucille Ball | Statement: [Follow the Fleet, starring, Lucille Ball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucille Ball
Context triple: [Follow the Fleet, starring, Lucille Ball]
  • A. Lucille Ball chosen
    Lucille Ball was an iconic American comedian, actress, and producer best known for starring in and co-creating the groundbreaking television sitcom "I Love Lucy."
  • B. Lucille Bliss
    Lucille Bliss was an American voice actress best known for her work in classic animated films and television, including early Disney productions and the original Smurfs series.
  • C. Betty Hutton
    Betty Hutton was a high-energy American film actress and singer best known for her comedic and musical roles in 1940s and 1950s Hollywood.
  • D. Gracie Allen
    Gracie Allen was an American comedian and actress best known as the zany, quick-witted partner and wife of George Burns in the classic Burns and Allen comedy team.
  • E. Martha Raye
    Martha Raye was an American comic actress and singer known for her brash, big-mouthed persona in film and television and for her extensive USO performances entertaining troops during multiple wars.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb2dfd3c81909b5e2996bc324301 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3078c0688190aefe179c5572721d completed March 9, 2026, 2:29 a.m.
Created at: March 4, 2026, 7:43 p.m.