Triple

T11985538
Position Surface form Disambiguated ID Type / Status
Subject Martin Short E285266 entity
Predicate tonyAwardFor P16597 FINISHED
Object Little Me E958333 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: Little Me | Statement: [Martin Short, tonyAwardFor, Little Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Little Me
Context triple: [Martin Short, tonyAwardFor, Little Me]
  • A. Little Me chosen
    "Little Me" is a comedic stage musical, with a book by Neil Simon and music by Cy Coleman, in which Martin Short notably starred in a celebrated revival.
  • B. Little My
    Little My is a small, fiercely independent and mischievous girl from Tove Jansson’s Moomin series, known for her sharp tongue, fearlessness, and distinctive topknot hairstyle.
  • C. Little Man
    "Little Man" is a stand-up comedy special by American comedian Gary Owen, showcasing his energetic storytelling and observational humor.
  • D. Little Man
    Little Man is a prominent subsidiary summit of Skiddaw in England’s Lake District, popular with hikers for its fine views and distinctive profile.
  • E. Little Man
    Little Man is a 2006 American comedy film starring Marlon Wayans as a diminutive criminal who poses as a baby to retrieve a stolen diamond.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903acbb9081908fe7f8360057785c completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48abcf2588190a44e6e31e045b356 completed May 1, 2026, 11:13 a.m.
Created at: April 8, 2026, 9:46 p.m.