Triple

T9801870
Position Surface form Disambiguated ID Type / Status
Subject My Bloody Valentine E237857 entity
Predicate screenwriter P2831 FINISHED
Object John Beaird
John Beaird is a screenwriter best known for his work on the 1981 Canadian slasher film "My Bloody Valentine."
 E821744 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: John Beaird | Statement: [My Bloody Valentine, screenwriter, John Beaird]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Beaird
Context triple: [My Bloody Valentine, screenwriter, John Beaird]
  • A. Baird Liddell
    Baird Liddell is an American jazz pianist and composer known for his contributions to modern jazz performance and recording.
  • B. Gordon Bethune
    Gordon Bethune is an American airline executive best known for leading the dramatic turnaround of Continental Airlines in the 1990s.
  • C. William Norrie
    William Norrie was a Canadian politician who served as the long-time mayor of Winnipeg, Manitoba.
  • D. Bruce McCulloch
    Bruce McCulloch is a Canadian actor, writer, and comedian best known as one of the core members of the sketch comedy troupe The Kids in the Hall.
  • E. John Bainbridge
    John Bainbridge was a 17th-century English astronomer and physician noted for his early telescopic observations and influential astronomical writings.
  • 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: John Beaird
Triple: [My Bloody Valentine, screenwriter, John Beaird]
Generated description
John Beaird is a screenwriter best known for his work on the 1981 Canadian slasher film "My Bloody Valentine."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Beaird
Target entity description: John Beaird is a screenwriter best known for his work on the 1981 Canadian slasher film "My Bloody Valentine."
  • A. Baird Liddell
    Baird Liddell is an American jazz pianist and composer known for his contributions to modern jazz performance and recording.
  • B. Gordon Bethune
    Gordon Bethune is an American airline executive best known for leading the dramatic turnaround of Continental Airlines in the 1990s.
  • C. William Norrie
    William Norrie was a Canadian politician who served as the long-time mayor of Winnipeg, Manitoba.
  • D. Bruce McCulloch
    Bruce McCulloch is a Canadian actor, writer, and comedian best known as one of the core members of the sketch comedy troupe The Kids in the Hall.
  • E. John Bainbridge
    John Bainbridge was a 17th-century English astronomer and physician noted for his early telescopic observations and influential astronomical writings.
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda62b41048190bcef70a7591830c6 completed April 1, 2026, 11:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c44edac48190a44fdfb858d0dbba completed April 5, 2026, 2:09 a.m.
NEDg Description generation batch_69d1c50af000819087d643cc41a6fcc8 completed April 5, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_69d1c5d39b288190b276371591a86399 completed April 5, 2026, 2:15 a.m.
Created at: March 30, 2026, 8:29 p.m.