Triple

T22095925
Position Surface form Disambiguated ID Type / Status
Subject Shadow of the Thin Man E546031 entity
Predicate featuresCharacter P626 FINISHED
Object Nick Charles NE NERFINISHED

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: Nick Charles | Statement: [Shadow of the Thin Man, featuresCharacter, Nick Charles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nick Charles
Context triple: [Shadow of the Thin Man, featuresCharacter, Nick Charles]
  • A. Nick Charles chosen
    Nick Charles is a witty, retired private detective best known as the charming protagonist of Dashiell Hammett’s mystery novel and film series "The Thin Man."
  • B. Paul Wiggin
    Paul Wiggin is a former American football defensive end and coach best known for his long NFL playing career with the Cleveland Browns and subsequent coaching roles at both the professional and college levels.
  • C. Charlie Hume
    Charlie Hume is the son of Desmond Hume in the television series "Lost."
  • D. Johnny Pearson
    Johnny Pearson was a British composer, pianist, and bandleader best known for his prolific library music work and memorable television themes.
  • E. Charlie Peters
    Charlie Peters is an American screenwriter and playwright known for his work on films such as "Three Men and a Little Lady."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e8f1f48190a5f1d9e96a6de688 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.