Triple

T4484326
Position Surface form Disambiguated ID Type / Status
Subject The Whip Hand E107198 entity
Predicate cinematographyBy P1953 FINISHED
Object Nicholas Musuraca E407598 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: Nicholas Musuraca | Statement: [The Whip Hand, cinematographyBy, Nicholas Musuraca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicholas Musuraca
Context triple: [The Whip Hand, cinematographyBy, Nicholas Musuraca]
  • A. Nicholas Musuraca chosen
    Nicholas Musuraca was an influential Italian-American cinematographer best known for his atmospheric, shadow-rich visual style that helped define classic film noir.
  • B. Paul De Meo
    Paul De Meo was an American screenwriter and producer best known for co-writing action and war-themed films and television projects, often in collaboration with J. Michael Straczynski and others.
  • C. Paul Merolla
    Paul Merolla is a neuroscientist and engineer best known as a co-founder of Neuralink, the neurotechnology company developing brain–computer interfaces.
  • D. John Femia
    John Femia is an actor known for playing the character Marshall Blechtman.
  • E. Dominic Fumusa
    Dominic Fumusa is an American actor known for his work in film, television, and theater, including prominent roles in projects like the series "Nurse Jackie" and various feature films.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a54c6c8190a7421bea6e3c00f1 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe41822c8190b406c192170af3d1 completed March 21, 2026, 8:23 p.m.
Created at: March 20, 2026, 12:58 p.m.