Triple

T9649686
Position Surface form Disambiguated ID Type / Status
Subject Bert Kalmar E233300 entity
Predicate notableWork P4 FINISHED
Object Three Little Words E44519 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: Three Little Words | Statement: [Bert Kalmar, notableWork, Three Little Words]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Three Little Words
Context triple: [Bert Kalmar, notableWork, Three Little Words]
  • A. Three Little Words chosen
    Three Little Words is a 1950 MGM musical film starring Fred Astaire and Red Skelton that dramatizes the real-life songwriting partnership of Bert Kalmar and Harry Ruby.
  • B. Only These Words
    "Only These Words" is a song featured on the album *Higher Truth* by Chris Cornell.
  • C. Thousand Words
    Thousand Words is an American film production company known for backing independent and critically acclaimed movies such as "Requiem for a Dream."
  • D. Don’t Say a Word
    "Don’t Say a Word" is a 2001 psychological thriller film about a psychiatrist racing to extract a crucial secret from a traumatized young woman to save his kidnapped daughter.
  • E. No More Words
    "No More Words" is a memoir by Reeve Lindbergh reflecting on the final years and declining health of her mother, aviator and author Anne Morrow Lindbergh.
  • 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_69ca848b31648190b57aa55da20285be completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9badd630819087fd844d7878ec61 completed April 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1826780fc81909c418e82bd94c581 completed April 4, 2026, 9:28 p.m.
Created at: March 30, 2026, 8:13 p.m.