Triple

T11243167
Position Surface form Disambiguated ID Type / Status
Subject The Cameraman E266125 entity
Predicate starring P1507 FINISHED
Object Marceline Day
Marceline Day was an American silent film actress best known for her leading roles in 1920s comedies and dramas, including opposite Buster Keaton.
 E913524 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: Marceline Day | Statement: [The Cameraman, starring, Marceline Day]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marceline Day
Context triple: [The Cameraman, starring, Marceline Day]
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Méjanelle
    Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
  • C. Hamelle
    Hamelle is a French music publishing house known for issuing important late-19th-century works, including major compositions by César Franck.
  • D. Tête-de-Boule
    Tête-de-Boule is a historical French exonym for the Atikamekw, an Indigenous people of the upper Saint-Maurice River region in Quebec, Canada.
  • E. Le Guignon
    Le Guignon is a poem by French writer Charles Baudelaire, included among his early poetic works.
  • 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: Marceline Day
Triple: [The Cameraman, starring, Marceline Day]
Generated description
Marceline Day was an American silent film actress best known for her leading roles in 1920s comedies and dramas, including opposite Buster Keaton.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marceline Day
Target entity description: Marceline Day was an American silent film actress best known for her leading roles in 1920s comedies and dramas, including opposite Buster Keaton.
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Méjanelle
    Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
  • C. Hamelle
    Hamelle is a French music publishing house known for issuing important late-19th-century works, including major compositions by César Franck.
  • D. Tête-de-Boule
    Tête-de-Boule is a historical French exonym for the Atikamekw, an Indigenous people of the upper Saint-Maurice River region in Quebec, Canada.
  • E. Le Guignon
    Le Guignon is a poem by French writer Charles Baudelaire, included among his early poetic works.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91b0b808190bc38008bb344d180 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad849f70819098a7056fbc4831ff completed April 19, 2026, 10:25 a.m.
NEDg Description generation batch_69e4b12eee348190bee6c84587e4955d completed April 19, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_69e4be2bb8c88190a21773b0c43b6b99 completed April 19, 2026, 11:36 a.m.
Created at: April 8, 2026, 9:30 p.m.