Triple

T15199291
Position Surface form Disambiguated ID Type / Status
Subject The Happy Prince E363221 entity
Predicate producer P490 FINISHED
Object Philippe Bober
Philippe Bober is a European film producer known for backing distinctive arthouse and auteur-driven cinema.
E1325229 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: Philippe Bober | Statement: [The Happy Prince, producer, Philippe Bober]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippe Bober
Context triple: [The Happy Prince, producer, Philippe Bober]
  • A. Philippe Borbouse
    Philippe Borbouse is a Belgian local politician who serves as the mayor of the municipality of Sombreffe.
  • B. Frédéric Bricout
    Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
  • C. Philippe Pemezec
    Philippe Pemezec is a French politician known for serving as mayor of the Parisian suburb Le Plessis-Robinson.
  • D. Philippe Knoche
    Philippe Knoche is a French business executive best known for leading the nuclear energy group Areva through a major restructuring of France’s atomic industry.
  • E. Philippe Renaldi
    Philippe Renaldi is the royal father of Mia Thermopolis in "The Princess Diaries," serving as the late Crown Prince whose legacy propels her unexpected journey into princesshood.
  • 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: Philippe Bober
Triple: [The Happy Prince, producer, Philippe Bober]
Generated description
Philippe Bober is a European film producer known for backing distinctive arthouse and auteur-driven cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Philippe Bober
Target entity description: Philippe Bober is a European film producer known for backing distinctive arthouse and auteur-driven cinema.
  • A. Philippe Borbouse
    Philippe Borbouse is a Belgian local politician who serves as the mayor of the municipality of Sombreffe.
  • B. Frédéric Bricout
    Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
  • C. Philippe Pemezec
    Philippe Pemezec is a French politician known for serving as mayor of the Parisian suburb Le Plessis-Robinson.
  • D. Philippe Knoche
    Philippe Knoche is a French business executive best known for leading the nuclear energy group Areva through a major restructuring of France’s atomic industry.
  • E. Philippe Renaldi
    Philippe Renaldi is the royal father of Mia Thermopolis in "The Princess Diaries," serving as the late Crown Prince whose legacy propels her unexpected journey into princesshood.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b476208190a5119710c518bb1f completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a040fc34f4c8190a1ae536e544b2543 completed May 13, 2026, 5:44 a.m.
NEDg Description generation batch_6a04123430308190af22a11b2151c8b8 completed May 13, 2026, 5:55 a.m.
NED2 Entity disambiguation (via description) batch_6a04131eb4988190af4024bfcad648bc completed May 13, 2026, 5:58 a.m.
Created at: April 10, 2026, 3:10 a.m.