Triple

T10737373
Position Surface form Disambiguated ID Type / Status
Subject Love, Rosie E253227 entity
Predicate musicBy P1952 FINISHED
Object Michael Beckmann
Michael Beckmann is a composer and musician known for creating film scores, including the soundtrack for the romantic comedy "Love, Rosie."
E899174 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: Michael Beckmann | Statement: [Love, Rosie, musicBy, Michael Beckmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Beckmann
Context triple: [Love, Rosie, musicBy, Michael Beckmann]
  • A. Michael Menzel
    Michael Menzel is a German board game illustrator and designer best known for creating the acclaimed cooperative game "Legends of Andor."
  • B. Eric Pohlmann
    Eric Pohlmann was an Austrian-born character actor best known for providing the original voice of the villain Ernst Stavro Blofeld in the early James Bond films.
  • C. Ben Becker
    Ben Becker is a German actor known for his intense screen presence and roles in both film and theater.
  • D. Michael Begler
    Michael Begler is an American television writer and producer best known for co-creating the period medical drama series "The Knick."
  • E. Michael Hecht
    Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
  • 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: Michael Beckmann
Triple: [Love, Rosie, musicBy, Michael Beckmann]
Generated description
Michael Beckmann is a composer and musician known for creating film scores, including the soundtrack for the romantic comedy "Love, Rosie."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michael Beckmann
Target entity description: Michael Beckmann is a composer and musician known for creating film scores, including the soundtrack for the romantic comedy "Love, Rosie."
  • A. Michael Menzel
    Michael Menzel is a German board game illustrator and designer best known for creating the acclaimed cooperative game "Legends of Andor."
  • B. Eric Pohlmann
    Eric Pohlmann was an Austrian-born character actor best known for providing the original voice of the villain Ernst Stavro Blofeld in the early James Bond films.
  • C. Ben Becker
    Ben Becker is a German actor known for his intense screen presence and roles in both film and theater.
  • D. Michael Begler
    Michael Begler is an American television writer and producer best known for co-creating the period medical drama series "The Knick."
  • E. Michael Hecht
    Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710410a04819090036597ac0d271c completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69e373af06588190879cd11cce11c7bb completed April 18, 2026, 12:06 p.m.
NEDg Description generation batch_69e378dcc92c8190952d4acfee2a309c completed April 18, 2026, 12:28 p.m.
NED2 Entity disambiguation (via description) batch_69e37be75a588190abb9569ef1e87279 completed April 18, 2026, 12:41 p.m.
Created at: April 8, 2026, 9:14 p.m.