Triple

T15393164
Position Surface form Disambiguated ID Type / Status
Subject To Catch a Killer E368099 entity
Predicate composer P1361 FINISHED
Object Paul Zaza E821746 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: Paul Zaza | Statement: [To Catch a Killer, composer, Paul Zaza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Zaza
Context triple: [To Catch a Killer, composer, Paul Zaza]
  • A. Paul Zaza chosen
    Paul Zaza is a Canadian film composer best known for his work on horror and genre films, including the score for "My Bloody Valentine."
  • B. Michael Vincenzo Gazzo
    Michael Vincenzo Gazzo was an American playwright and character actor best known for his Oscar-nominated role as Frank Pentangeli in "The Godfather Part II."
  • C. Cristian Zorzi
    Cristian Zorzi is an Italian former cross-country skier best known for winning Olympic and World Championship medals, particularly as a sprint specialist and key member of Italy’s relay teams in the late 1990s and 2000s.
  • D. Alfredo Zanetti
    Alfredo Zanetti was a mountaineer known for making the first ascent of the challenging Cassin's Ridge route.
  • E. Valerio Zurlini
    Valerio Zurlini was an Italian film director and screenwriter known for his visually poetic, melancholic dramas such as "Girl with a Suitcase" and "The Desert of the Tartars."
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e7838b48190862b43c6c8620692 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1350699c8190acf7830d88455851 completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.