Triple

T11733681
Position Surface form Disambiguated ID Type / Status
Subject Emmanuelle Vaugier E278969 entity
Predicate notableWork P4 FINISHED
Object Saw II E289133 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: Saw II | Statement: [Emmanuelle Vaugier, notableWork, Saw II]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saw II
Context triple: [Emmanuelle Vaugier, notableWork, Saw II]
  • A. Saw II chosen
    Saw II is a 2005 horror film in the Saw franchise, known for its elaborate death traps and psychological games orchestrated by the serial killer Jigsaw.
  • B. Saw III
    Saw III is a 2006 American horror film in the Saw franchise, known for its elaborate traps, graphic violence, and continuation of the Jigsaw killer’s storyline.
  • C. Saw VI
    Saw VI is a 2009 American horror film in the Saw franchise that continues the story of the Jigsaw Killer’s gruesome moral tests and traps.
  • D. Saw
    Saw is a 2004 horror film that launched a popular franchise known for its psychological terror, elaborate death traps, and twist ending.
  • E. Saw IV
    Saw IV is a 2007 American horror film in the Saw franchise, continuing the series’ elaborate trap-based storyline and psychological terror.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4daa7f48190896fc7653e9dd70b completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8406fe8881909722ecb040087e68 completed April 27, 2026, 3:43 p.m.
Created at: April 8, 2026, 9:41 p.m.