Triple

T12138971
Position Surface form Disambiguated ID Type / Status
Subject Saw II E289133 entity
Predicate follows P134 FINISHED
Object Saw E286709 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 | Statement: [Saw II, follows, Saw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saw
Context triple: [Saw II, follows, Saw]
  • A. Saw chosen
    Saw is a 2004 horror film that launched a popular franchise known for its psychological terror, elaborate death traps, and twist ending.
  • B. Saw film series
    The Saw film series is a long-running American horror franchise known for its elaborate death traps, moralistic games, and the iconic serial killer Jigsaw.
  • C. 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.
  • D. Saw 3D
    Saw 3D is a 2010 American horror film in the Saw franchise, marketed as the series’ first 3D installment and intended as a concluding chapter to the long-running torture-porn saga.
  • E. 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.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158eef48819083bdce283a363414 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a81f6708190a6a215421f8ce8dd completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:49 p.m.