Triple

T10737369
Position Surface form Disambiguated ID Type / Status
Subject Love, Rosie E253227 entity
Predicate cinematographyBy P1953 FINISHED
Object Christian Rein
Christian Rein is a cinematographer best known for his work on the romantic comedy-drama film "Love, Rosie."
E883685 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: Christian Rein | Statement: [Love, Rosie, cinematographyBy, Christian Rein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christian Rein
Context triple: [Love, Rosie, cinematographyBy, Christian Rein]
  • A. Christian Brandauer
    Christian Brandauer is the son of Austrian actor and director Klaus Maria Brandauer.
  • B. Christian Rapp
    Christian Rapp is a Dutch architect known for his role in the redevelopment and urban design of Amsterdam’s KNSM Island.
  • C. Christian Natter
    Christian Natter is an Austrian local politician who serves as the mayor of the municipality of Wolfurt in the state of Vorarlberg.
  • D. Christian Meyer
    Christian Meyer is the husband of American author Stephenie Meyer, best known for her Twilight series.
  • E. Robert Reinick
    Robert Reinick was a 19th-century German poet and painter associated with the Düsseldorf school, known for providing texts for musical works by composers such as Robert Schumann.
  • 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: Christian Rein
Triple: [Love, Rosie, cinematographyBy, Christian Rein]
Generated description
Christian Rein is a cinematographer best known for his work on the romantic comedy-drama film "Love, Rosie."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Christian Rein
Target entity description: Christian Rein is a cinematographer best known for his work on the romantic comedy-drama film "Love, Rosie."
  • A. Christian Brandauer
    Christian Brandauer is the son of Austrian actor and director Klaus Maria Brandauer.
  • B. Christian Rapp
    Christian Rapp is a Dutch architect known for his role in the redevelopment and urban design of Amsterdam’s KNSM Island.
  • C. Christian Natter
    Christian Natter is an Austrian local politician who serves as the mayor of the municipality of Wolfurt in the state of Vorarlberg.
  • D. Christian Meyer
    Christian Meyer is the husband of American author Stephenie Meyer, best known for her Twilight series.
  • E. Robert Reinick
    Robert Reinick was a 19th-century German poet and painter associated with the Düsseldorf school, known for providing texts for musical works by composers such as Robert Schumann.
  • 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_69de22dce1cc8190a3511d86e8bd6d3e completed April 14, 2026, 11:19 a.m.
NEDg Description generation batch_69de271e2698819093bba748a0a0db5d completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2cdd79608190bad8045939556bc7 completed April 14, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:14 p.m.