Triple

T5741313
Position Surface form Disambiguated ID Type / Status
Subject License to Wed E126619 entity
Predicate character P662 FINISHED
Object Ben Murphy
Ben Murphy is a fictional character from the romantic comedy film "License to Wed," serving as one of the supporting roles in the story.
 E543073 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: Ben Murphy | Statement: [License to Wed, character, Ben Murphy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ben Murphy
Context triple: [License to Wed, character, Ben Murphy]
  • A. Mark Curtis
    Mark Curtis is a British historian and author known for his critical works on UK foreign policy and Western interventionism.
  • B. Bill Durnan
    Bill Durnan was a Hall of Fame Canadian goaltender for the Montreal Canadiens in the 1940s, renowned for his ambidextrous catching ability and dominance in the early NHL.
  • C. Berry Murphy
    Berry Murphy is the child of Irish actor Aidan Gillen, known for his roles in series like "Game of Thrones" and "The Wire."
  • D. Lex Murphy
    Lex Murphy is a young, tech-savvy girl who becomes one of the central child protagonists surviving the dinosaur chaos in the Jurassic Park franchise.
  • E. John Bishop
    John Bishop is an English stand-up comedian, actor, and television presenter known for his energetic storytelling style and appearances on British panel shows and dramas.
  • 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: Ben Murphy
Triple: [License to Wed, character, Ben Murphy]
Generated description
Ben Murphy is a fictional character from the romantic comedy film "License to Wed," serving as one of the supporting roles in the story.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ben Murphy
Target entity description: Ben Murphy is a fictional character from the romantic comedy film "License to Wed," serving as one of the supporting roles in the story.
  • A. Mark Curtis
    Mark Curtis is a British historian and author known for his critical works on UK foreign policy and Western interventionism.
  • B. Bill Durnan
    Bill Durnan was a Hall of Fame Canadian goaltender for the Montreal Canadiens in the 1940s, renowned for his ambidextrous catching ability and dominance in the early NHL.
  • C. Berry Murphy
    Berry Murphy is the child of Irish actor Aidan Gillen, known for his roles in series like "Game of Thrones" and "The Wire."
  • D. Lex Murphy
    Lex Murphy is a young, tech-savvy girl who becomes one of the central child protagonists surviving the dinosaur chaos in the Jurassic Park franchise.
  • E. John Bishop
    John Bishop is an English stand-up comedian, actor, and television presenter known for his energetic storytelling style and appearances on British panel shows and dramas.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0258382908190af8787feb1e5fbcd completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e1bfe4481908740aa20d55ec8f6 completed March 22, 2026, 11:41 p.m.
NEDg Description generation batch_69c08a2bc1b08190998a7e5eb8d6d6ac completed March 23, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_69c08a85b508819088464b97b6c9bb99 completed March 23, 2026, 12:34 a.m.
Created at: March 22, 2026, 3:48 p.m.