Triple

T2664136
Position Surface form Disambiguated ID Type / Status
Subject Mark Burg E55591 entity
Predicate notableWork P4 FINISHED
Object Saw V
Saw V is a 2008 American horror film in the Saw franchise, continuing the series’ elaborate trap-based killings and intricate storyline following the legacy of the Jigsaw Killer.
 E295572 NE FINISHED

How this triple was built (4 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 V | Statement: [Mark Burg, notableWork, Saw V]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saw V
Context triple: [Mark Burg, notableWork, Saw V]
  • A. 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.
  • B. Saw
    Saw is a 2004 horror film that launched a popular franchise known for its psychological terror, elaborate death traps, and twist ending.
  • C. Saw IV
    Saw IV is a 2007 American horror film in the Saw franchise, continuing the series’ elaborate trap-based storyline and psychological terror.
  • D. Saw II
    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.
  • E. SawTeen See
    SawTeen See is a prominent structural engineer known for her work on major skyscraper projects and for her long professional and personal partnership with fellow engineer Leslie E. Robertson.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Saw V
Triple: [Mark Burg, notableWork, Saw V]
Generated description
Saw V is a 2008 American horror film in the Saw franchise, continuing the series’ elaborate trap-based killings and intricate storyline following the legacy of the Jigsaw Killer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saw V
Target entity description: Saw V is a 2008 American horror film in the Saw franchise, continuing the series’ elaborate trap-based killings and intricate storyline following the legacy of the Jigsaw Killer.
  • A. 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.
  • B. Saw
    Saw is a 2004 horror film that launched a popular franchise known for its psychological terror, elaborate death traps, and twist ending.
  • C. Saw IV
    Saw IV is a 2007 American horror film in the Saw franchise, continuing the series’ elaborate trap-based storyline and psychological terror.
  • D. Saw II
    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.
  • E. SawTeen See
    SawTeen See is a prominent structural engineer known for her work on major skyscraper projects and for her long professional and personal partnership with fellow engineer Leslie E. Robertson.
  • F. None of above. chosen

Provenance (5 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96dba44819085c3e651afba7806 completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbb50cec8190aea067e486a5b092 completed March 10, 2026, 6:35 a.m.
NEDg Description generation batch_69afbce109f48190be1a31d9300dbee6 completed March 10, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69afbda490ac8190bb12598e26b91677 completed March 10, 2026, 6:43 a.m.
Created at: March 6, 2026, 9:54 p.m.